Canary in a coal mine: perceptions of climate change risks and response options among Canadian mine operations

A survey documenting how climate change is perceived and responded to by Canadian mine operations was administered to a random sample of practitioners working at mine sites across Canada. Key findings include: (1) Mines are sensitive to climatic hazards; (2) There is concern about climate change among mine practitioners, but the majority have not yet noticed climate change to be affecting operations; (3) Future climate change is expected to have negative impacts for mine operations; (4) Mines are responding to climate change mainly through efforts to reduce greenhouse gas emissions but also through adaptation, although to a lesser degree; and (5) Knowledge of future climate change projections and impacts is limited, potentially constraining understanding of the nature of climate change risks. The survey compliments previous work documenting perceptions among upper level management on climate change in the Canadian mining industry. The results from both surveys are largely consistent, establishing that the mining sector perceives climate change as an emerging risk and is developing response options, but needs to invest more time and resources for adaptation to what are inevitable changes in climate. The results support the need for targeted in-depth research to assess the vulnerability of mining to climate change and to evaluate response options.     

Efficient risk assessment of lifeline networks under spatially correlated ground motions using selective recursive decomposition algorithm

For effective hazard mitigation planning and prompt-but-prudent post-disaster responses, it is essential to evaluate the reliability of infrastructure networks accurately and efficiently. A nonsimulation-based algorithm, termed as a recursive decomposition algorithm (RDA), was recently proposed to identify disjoint cut sets and link sets and to compute the network reliability. This paper introduces a ‘selective’ RDA, which preferentially identifies critical disjoint cut sets and link sets to calculate the probabilities of network disconnection events with a significantly reduced number of identified sets. To this end, the original RDA is improved by replacing the shortest path algorithm with an algorithm that identifies the most reliable path, and by using a graph decomposition scheme based on the probabilities associated with the subgraphs. The critical sets identified by the algorithm are also used to compute conditional probability-based importance measures that quantify the relative importance of network components by their contributions to network disconnection events. This paper also introduces a risk assessment framework for lifeline networks based on the use of the selective RDA, which can consider both interevent and intraevent uncertainties of spatially correlated ground motions. The risk assessment framework and the selective RDA are demonstrated by a hypothetical network example, and the gas and water transmission networks of Shelby County in Tennessee, USA. The examples show that the proposed framework and the selective RDA greatly improve efficiency of risk assessment of complex lifeline networks, which are characterized by a large number of components, complex network topology, and statistical dependence between component failures. Copyright © 2012 John Wiley & Sons, Ltd.     

Extreme temperature scenarios in Mexicali,Mexico under climate change conditions

Extreme weather events can have severe consequences for the population and the environment. Therefore, in this study a temporal trend of annual temperatures was built with a time series from 1950 to 2010 for Mexicali, Mexico, and estimates of 5- to 100-year return periods are provided by modeling of summer maximum and winter minimum temperatures. A non-parametric Kendall’s tau test and the Sen’s slope estimator were used to compute trends. The generalized extreme value (GEV) distribution was applied to the approximation of block maxima and the generalized Pareto distribution (GPD) to values over a predetermined threshold. Due to the non-stationary characteristic of the series of temperature values, the temporal trend was included as a covariable in the location parameter and substantial improvements were observed, particularly with the extreme minimum temperature, compared to that obtained with the GEV with no covariable and with the GPD. A positive and significant statistically trend in both summer maximum temperature and winter minimum temperature was found. By the end of 21st century the extreme maximum temperature could be 2 to 3 °C higher than current, and the winter could be less severe, as the probabilistic model suggests increases of 7 to 9 °C in the extreme minimum temperature with respect to the base period. The foreseeable consequences on Mexicali city are discussed.     

Effects of natural and calcined poultry waste on Cd, Pb and As mobility in contaminated soil

The reuse of waste materials as soil additives could be a welcome development in soil remediation. The mobility of Cd, Pb and As in a contaminated soil was investigated using natural and calcined poultry wastes (eggshell and chicken bone), CaCO₃ and CaO at different application rates (0, 1, 3 and 5 %). The chemical composition accompanied with mineralogical composition indicated that CaCO₃ and CaO were the major components in natural and calcined eggshells, respectively, while hydroxyapatite (HAP) dominated the natural and calcined chicken bones. The results showed that soil pH tended to increase in response to increasing application rates of all soil additives. The effectiveness of the additives in reducing Cd, Pb and As mobility was assessed by means of chemical extractions with 0.1 N HCl for Cd and Pb or 1 N HCl for As, according to Korean Standard Test (KST) method. Both calcined eggshell and chicken bone were equally effective with CaO or CaCO₃ in reducing the concentration of 0.1 N HCl-extractable Cd from 6.17 mg kg^?1 to below warning level of 1.5 mg kg^?1, especially at the highest application rate. The application of calcined eggshell, CaO and CaCO₃ also decreased the concentration of 0.1 N HCl-extractable Pb from 1,012 mg kg^?1 to below warning level of 100 mg kg^?1. The Pb concentration decreased significantly with an increasing application rate of chicken bone, but remained above warning level even at the highest application rate. On the contrary, natural and calcined chicken bones led to a significant increase in the mobility of As when compared with the control soil. These findings illustrate that calcined eggshell in particular is equally effective as pure chemical additives in stabilizing Cd and Pb in a contaminated agricultural soil. The presence of As in metal-contaminated soils should be taken into consideration when applying phosphate-containing materials as soil additives, because phosphate can compete with arsenate on adsorption sites and result in As mobilization.     

Analysis and characterization of the synergistic AIRS and MODIS cloud-cleared radiances

The Atmospheric Infrared Sounder (AIRS) and MODerate-Resolution Imaging Spectroradiometer (MODIS) on board NASA Earth Observing System (EOS) Aqua spacecraft measure the upwelling infrared radiance used for numerous remote-sensing- and climate-related applications. AIRS provides high spectral resolution infrared radiances, while MODIS provides collocated high spatial resolution radiances at 16 broad infrared bands. An optimal algorithm for cloud-clearing has been developed for AIRS cloudy soundings at the University of Wisconsin-Madison, where the spatially and spectrally collocated AIRS and MODIS data has been used to analyze the characteristic of this algorithm. An analysis and characterization of the global AIRS cloud-cleared radiances using the bias and the standard deviation between the cloud-cleared and the nearby clear measurements are studied. Scene inhomogeneity for both land- and water-surface types has been estimated to account for the assessed error. Both monthly and seasonal changes of global AIRS/MODIS cloud-clearing performance also have been analyzed.     

Post-independence population planning and social development in Singapore

The unique and remarkable post-independence demographic transition of Singapore, from high to low growth, has been accompanied by an equally spectacular social transformation. Both population control and social change have a positive impact on the fertility trend. Singapore's population policy has been dictated much by the crisis consciousness of the leadership which has been able to create a high degree of awareness among its population with regard to fertility.Ironically, public response to the government's population control has been too successful, particularly so among the upper-income groups. This has recently prompted the government to examine the sustained low fertility rate which, if unchecked, will bear serious social, economic, political and defence consequences in 20 to 30 years time. The aim of the current fertility campaign is to reachieve the replacement level, first reached in 1975, through the correction of the lopsided procreation pattern. As such, some disincentives have remained or been removed, while several new incentives and measures have been introduced. Observations are made with regard to the future fertility trends.     

Origin of complex zoning in olivine from diverse,diamondiferous kimberlites and tectonic settings: Ekati (Canada), Alto Paranaiba (Brazil) and Kaalvallei (South Africa)

Olivine in kimberlites can provide unique insights into magma petrogenesis, because it is the most abundant xenocrystic phase and a stable magmatic product over most of the liquid line of descent. In this study we examined the petrography and chemistry of olivine in kimberlites from different tectonic settings, including the Slave craton, Canada (Ekati: Grizzly, Koala), the Brasilia mobile belt (Limpeza-18, Tres Ranchos-04), and the Kaapvaal craton, South Africa (Kaalvallei: Samada, New Robinson). Olivine cores display a wide range of compositions (e.g., Mg# = 78–95). The similarity in olivine composition, resorption of core zones and inclusions of mantle-derived phases, indicates that most olivine cores originated from the disaggregation of mantle peridotites, including kimberlite-metasomatised lithologies (i.e. sheared lherzolites and megacrysts). Olivine rims typically show a restricted range of Mg#, with decreasing Ni and increasing Mn and Ca contents, a characteristic of kimberlitic olivine worldwide. The rims host inclusions of groundmass minerals, which implies crystallisation just before and/or during emplacement. There is a direct correlation between olivine rim composition and groundmass mineralogy, whereby high Mg/Fe rims are associated with carbonate-rich kimberlites, and lower Mg/Fe rims are correlated with increased phlogopite and Fe-bearing oxide mineral abundances. There are no differences in olivine composition between explosive (Grizzly) and hypabyssal (Koala) kimberlites. Olivine in kimberlites also displays transitional zones and less common internal zones, between cores and rims. The diffuse transitional zones exhibit intermediate compositions between cores and rims, attributed to partial re-equilibration of xenocrystic cores with the ascending kimberlite melt. In contrast, internal zones form discrete layers with resorbed margins and restricted Mg# values, but variable Ni, Mn and Ca concentrations, which indicates a discrete crystallization event from precursor kimberlite melts at mantle depths. Overall, olivine exhibits broadly analogous zoning in kimberlites worldwide. Variable compositions for individual zones relate to different parental melt compositions rather than variations in tectonic setting or emplacement mechanism.

     

Automated Kerogen Classification in Microscope Images of Dispersed Kerogen Preparation

We develop the classification part of a system that analyses transmitted light microscope images of dispersed kerogen preparation. The system automatically extracts kerogen pieces from the image and labels each piece as either inertinite or vitrinite. The image pre-processing analysis consists of background removal, identification of kerogen material, object segmentation, object extraction (individual images of pieces of kerogen) and feature calculation for each object. An expert palynologist was asked to label the objects into categories inertinite and vitrinite, which provided the ground truth for the classification experiment. Ten state-of-the-art classifiers and classifier ensembles were compared: Naïve Bayes, decision tree, nearest neighbour, the logistic classifier, multilayered perceptron (MLP), support vector machines (SVM), AdaBoost, Bagging, LogitBoost and Random Forest. The logistic classifier was singled out as the most accurate classifier, with an accuracy greater than 90. Using a 10 times 10-fold cross-validation provided within the Weka software, we found that the logistic classifier was significantly better than five classifiers (p<0.05) and indistinguishable from the other four classifiers. The initial set of 32 features was subsequently reduced to 6 features without compromising the classification accuracy. A further evaluation of the system alerted us to the possible sensitivity of the classification to the ground truth that might vary from one human expert to another. The analysis also revealed that the logistic classifier made most of the correct classifications with a high certainty.     

Stability of Kerogen Classification with Regard to Image Segmentation

This paper investigates the stability of an automatic system for classifying kerogen material from images of sieved rock samples. The system comprises four stages: image acquisition, background removal, segmentation, and classification of the segmented kerogen pieces as either inertinite or vitrinite. Depending upon a segmentation parameter d, called “overlap”, touching pieces of kerogen may be split differently. The aim of this study is to establish how robust the classification result is to variations of the segmentation parameter. There are two issues that pose difficulties in carrying out an experiment. First, even a trained professional may be uncertain when distinguishing between isolated pieces of inertinite and vitrinite, extracted from transmitted-light microscope images. Second, because manual labelling of large amount of data for training the system is an arduous task, we acquired the true labels (ground truth) only for the pieces obtained at overlap d=0.5. To construct ground truth for various values of d we propose here label-inheritance trees. With thus estimated ground truth, an experiment was carried out to evaluate the robustness of the system to changes in the segmentation through varying the overlap value d. The average system accuracy across values of d spanning the range from 0 to 1 was 86.5%, which is only slightly lower than the accuracy of the system at the design value of d=0.5 (89.07%).     

Development of groundwater favourability map using GIS-based driven data mining models: an approach for effective groundwater resource management

The development of groundwater favourability map is an effective tool for the sustainability management of groundwater resources in typical agricultural regions, such as southern Perak Province, Malaysia. Assessing the potentiality and pollution vulnerability of groundwater is a fundamental phase of favourability mapping. A geographic information system (GIS)-based Boolean operator of a spatial analyst module was applied to combine a groundwater potentiality map (GPM) model and a groundwater vulnerability to pollution index (GVPI) map, thereby establishing the favourable zones for drinking water exploration in the investigated area. The area GPM model was evaluated by applying a GIS-based Dempster–Shafer–evidential belief function model. In the evaluation, six geoelectrically determined groundwater potential conditioning factors (i.e. overburden resistivity, overburden thickness, aquifer resistivity, aquifer thickness, aquifer transmissivity and hydraulic conductivity) were synthesized by employing the probability-based algorithms of the model. The generated thematic maps of the seven hydrogeological parameters of the DRASTIC model were considered as pollution potential conditioning factors and were analysed with the developed ordered weighted average–DRASTIC index model algorithms to construct the GVPI map. Approximately 88.8 and 85.71% prediction accuracies for the Groundwater Potentiality and GVPI maps were established using the reacting operating characteristic curve method and water quality status–vulnerability zone relationship scheme, respectively. Finally, the area groundwater favourability map (GFM) model was produced by applying a GIS-based Boolean operator on the Groundwater Potentiality and GVPI maps. The GFM model reveals three distinct zones: ‘not suitable’, ‘less suitable’ and ‘very suitable’ zones. The area analysis of the GFM model indicates that more than 50% of the study area is covered by the ‘very suitable’ zones. Results produce a suitability map that can be used by local authorities for the exploitation and management of drinking water in the area. The study findings can also be applied as a tool to help increase public awareness of groundwater issues in developing countries.