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Déja vu and Wind Turbines: A Review of Lived Experiences after Appeals of Ontario Industrial-Scale Wind Power Facilities  [PDF]
Jane Wilson, Carmen Krogh, Paula C. Peel
Open Access Library Journal (OALib Journal) , 2020, DOI: 10.4236/oalib.1106276
Abstract: This paper is a review of reports of lived experiences of residents in rural/small-town Ontario, Canada and a comparison to the concerns raised during citizen-sponsored appeals of industrial-scale wind power project approvals. We found that the concerns leading to the decisions to appeal power projects have been borne out in real-life experience, as government documents record thousands of complaints about adverse effects on the environment and human health. These findings support the need for enforcement of regulations on wind power operations, and the need to acknowledge that community concerns about large power projects are genuine.
Yochelcionella (Mollusca, Helcionelloida) from the lower Cambrian of North America
Atkins C J,Peel J S
Bulletin of Geosciences , 2008, DOI: 10.3140/bull.geosci.2008.01.023
Abstract: Five named species of the helcionelloid mollusc genus Yochelcionella Runnegar & Pojeta, 1974 are recognized from the lower Cambrian (Cambrian Series 2) of North America: Yochelcionella erecta (Walcott, 1891), Y. americana Runnegar &Pojeta, 1980, Y. chinensis Pei, 1985, Y. greenlandica Atkins & Peel, 2004 and Y. gracilis Atkins & Peel, 2004, linking lower Cambrian outcrops along the present north-eastern seaboard. Yochelcionella erecta, an Avalonian species, is described for the first time; other species are derived from Laurentia. A revised concept of the Chinese species, Y. chinensis, is based mainly on a large sample from the Forteau Formation of western Newfoundland and the species may have stratigraphic utility between Cambrian palaeocontinents.
New constraints on the Polarization of Anomalous Microwave Emission in nearby molecular clouds
C. Dickinson,M. W. Peel,M. Vidal
Physics , 2011, DOI: 10.1111/j.1745-3933.2011.01138.x
Abstract: Anomalous Microwave Emission (AME) has been previously studied in two well-known molecular clouds and is thought to be due to electric dipole radiation from small spinning dust grains. It is important to measure the polarization properties of this radiation both for component separation in future cosmic microwave background experiments and also to constrain dust models. We have searched for linearly polarized radio emission associated with the $\rho$ Ophiuchi and Perseus molecular clouds using {\it WMAP} 7-year data. We found no significant polarization within an aperture of $2^{\circ}$ diameter. The upper limits on the fractional polarization of spinning dust in the $\rho$ Ophiuchi cloud are 1.7%, 1.6% and 2.6% (at 95% confidence level) at K-, Ka- and Q-bands, respectively. In the Perseus cloud we derived upper limits of 1.4%, 1.9% and 4.7%, at K-, Ka- and Q-bands, respectively; these are similar to those found by L\'opez-Caraballo et al. If AME at high Galactic latitudes has a similarly low level of polarization, this will simplify component separation for CMB polarization measurements. We can also rule out single domain magnetic dipole radiation as the dominant emission mechanism for the 20-40 GHz. The polarization levels are consistent with spinning dust models.
Updated world map of the K ppen-Geiger climate classification
M. C. Peel, B. L. Finlayson,T. A. McMahon
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2007,
Abstract: Although now over 100 years old, the classification of climate originally formulated by Wladimir K ppen and modified by his collaborators and successors, is still in widespread use. It is widely used in teaching school and undergraduate courses on climate. It is also still in regular use by researchers across a range of disciplines as a basis for climatic regionalisation of variables and for assessing the output of global climate models. Here we have produced a new global map of climate using the K ppen-Geiger system based on a large global data set of long-term monthly precipitation and temperature station time series. Climatic variables used in the K ppen-Geiger system were calculated at each station and interpolated between stations using a two-dimensional (latitude and longitude) thin-plate spline with tension onto a 0.1°×0.1° grid for each continent. We discuss some problems in dealing with sites that are not uniquely classified into one climate type by the K ppen-Geiger system and assess the outcomes on a continent by continent basis. Globally the most common climate type by land area is BWh (14.2%, Hot desert) followed by Aw (11.5%, Tropical savannah). The updated world K ppen-Geiger climate map is freely available electronically in the Supplementary Material Section.
Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis
T. A. McMahon,M. C. Peel,L. Lowe,R. Srikanthan
Hydrology and Earth System Sciences Discussions , 2012, DOI: 10.5194/hessd-9-11829-2012
Abstract: This guide to estimating daily and monthly actual, potential, reference crop and pan evaporation covers topics that are of interest to researchers, consulting hydrologists and practicing engineers. Topics include estimating actual evaporation from deep lakes and from farm dams and for catchment water balance studies, estimating potential evaporation as input to rainfall-runoff models, and reference crop evapotranspiration for small irrigation areas, and for irrigation within large irrigation districts. Inspiration for this guide arose in response to the authors' experiences in reviewing research papers and consulting reports where estimation of the actual evaporation component in catchment and water balance studies was often inadequately handled. Practical guides using consistent terminology that cover both theory and practice are not readily available. Here we provide such a guide, which is divided into three parts. The first part provides background theory and an outline of conceptual models of potential evaporation of Penman, Penman-Monteith and Priestley-Taylor, and discussions of reference crop evaporation and then Class-A pan evaporation. The last two sub-sections in this first part include techniques to estimate actual evaporation from (i) open-surface water and (ii) landscapes and catchments (Morton and the advection-aridity models). The second part addresses topics confronting a practicing hydrologist, e.g. estimating actual evaporation for deep lakes, shallow lakes and farm dams, lakes covered with vegetation, catchments, irrigation areas and bare soil. The third part addresses six related issues (i) hard-wired evaporation estimates, (ii) evaporation estimates without wind data, (iii) at-site meteorological data, (iv) dealing with evaporation in a climate change environment, (v) 24-h versus day-light hour estimation of meteorological variables, and (vi) uncertainty in evaporation estimates. This paper is supported by supplementary material that includes 21 appendices enhancing the material in the text, worked examples of many procedures discussed in the paper, a program listing (Fortran 90) of Morton's WREVAP evaporation models along with tables of monthly Class-A pan coefficients for 68 locations across Australia and other information.
Updated world map of the K ppen-Geiger climate classification
M. C. Peel,B. L. Finlayson,T. A. McMahon
Hydrology and Earth System Sciences Discussions , 2007,
Abstract: Although now over 100 years old, the classification of climate originally formulated by Wladimir K ppen and modified by his collaborators and successors, is still in widespread use. It is widely used in teaching school and undergraduate courses on climate. It is also still in regular use by researchers across a range of disciplines as a basis for climatic regionalisation of variables and for assessing the output of global climate models. Here we have produced a new global map of climate using the K ppen-Geiger system based on a large global data set of long-term monthly precipitation and temperature station time series. Climatic variables used in the K ppen-Geiger system were calculated at each station and interpolated between stations using a two-dimensional (latitude and longitude) thin-plate spline with tension onto a 0.1°×0.1° grid for each continent. We discuss some problems in dealing with sites that are not uniquely classified into one climate type by the K ppen-Geiger system and assess the outcomes on a continent by continent basis. Globally the most common climate type by land area is BWh (14.2%, Hot desert) followed by Aw (11.5%, Tropical savannah). The updated world K ppen-Geiger climate map is freely available electronically at http://www.hydrol-earth-syst-sci.net/????.
Simulations and Observations of the Microwave Universe
Michael Peel
Physics , 2010,
Abstract: [Abridged] Simulations and observations of the microwave sky are of great importance for understanding the Universe that we reside in. Specifically, knowledge of the CMB and its foregrounds - including the SZ effect from clusters of galaxies and radio point sources - tell us about the Universe on its very largest scales, and also what the Universe is made of. We describe the creation of software to carry out large numbers of virtual sky simulations. The simulations include the CMB, SZ effect and point sources, and are designed to examine the effects of point sources and the SZ effect on present and recent observations of the CMB. Utilizing sets of 1,000 simulations, we find that the power spectrum resulting from the SZ effect is expected to have a larger standard deviation by a factor of 3 than would be expected from purely Gaussian realizations, and is significantly skewed towards increased values for the power spectrum. The effects of the clustering of galaxy clusters, residual point sources and uncertainties in the gas physics are also investigated, as are the implications for the excess power measured in the CMB power spectrum by the CBI and BIMA. We carry out end-to-end simulations for OCRA-p observations of point sources. The introduction of simulated 1/ f noise significantly reduces the predicted ability of the instruments to observe weak sources by measuring the sources for long periods of time. The OCRA-p receiver has been used to observe point sources in the VSA fields so that they can be subtracted from observations of the CMB power spectrum. We find that these point sources are split between steep and flat spectrum sources. We have also observed 550 CRATES flat spectrum radio sources, which will be useful for comparison to Planck satellite observations. Finally, the assembly and commissioning of the OCRA-F receiver is outlined. [Abridged]
Topological Feature Based Classification
Leto Peel
Computer Science , 2011,
Abstract: There has been a lot of interest in developing algorithms to extract clusters or communities from networks. This work proposes a method, based on blockmodelling, for leveraging communities and other topological features for use in a predictive classification task. Motivated by the issues faced by the field of community detection and inspired by recent advances in Bayesian topic modelling, the presented model automatically discovers topological features relevant to a given classification task. In this way, rather than attempting to identify some universal best set of clusters for an undefined goal, the aim is to find the best set of clusters for a particular purpose. Using this method, topological features can be validated and assessed within a given context by their predictive performance. The proposed model differs from other relational and semi-supervised learning models as it identifies topological features to explain the classification decision. In a demonstration on a number of real networks the predictive capability of the topological features are shown to rival the performance of content based relational learners. Additionally, the model is shown to outperform graph-based semi-supervised methods on directed and approximately bipartite networks.
Active Discovery of Network Roles for Predicting the Classes of Network Nodes
Leto Peel
Computer Science , 2013,
Abstract: Nodes in real world networks often have class labels, or underlying attributes, that are related to the way in which they connect to other nodes. Sometimes this relationship is simple, for instance nodes of the same class are may be more likely to be connected. In other cases, however, this is not true, and the way that nodes link in a network exhibits a different, more complex relationship to their attributes. Here, we consider networks in which we know how the nodes are connected, but we do not know the class labels of the nodes or how class labels relate to the network links. We wish to identify the best subset of nodes to label in order to learn this relationship between node attributes and network links. We can then use this discovered relationship to accurately predict the class labels of the rest of the network nodes. We present a model that identifies groups of nodes with similar link patterns, which we call network roles, using a generative blockmodel. The model then predicts labels by learning the mapping from network roles to class labels using a maximum margin classifier. We choose a subset of nodes to label according to an iterative margin-based active learning strategy. By integrating the discovery of network roles with the classifier optimisation, the active learning process can adapt the network roles to better represent the network for node classification. We demonstrate the model by exploring a selection of real world networks, including a marine food web and a network of English words. We show that, in contrast to other network classifiers, this model achieves good classification accuracy for a range of networks with different relationships between class labels and network links.
Estimating Network Parameters for Selecting Community Detection Algorithms
Leto Peel
Computer Science , 2010,
Abstract: This paper considers the problem of algorithm selection for community detection. The aim of community detection is to identify sets of nodes in a network which are more interconnected relative to their connectivity to the rest of the network. A large number of algorithms have been developed to tackle this problem, but as with any machine learning task there is no "one-size-fits-all" and each algorithm excels in a specific part of the problem space. This paper examines the performance of algorithms developed for weighted networks against those using unweighted networks for different parts of the problem space (parameterised by the intra/inter community links). It is then demonstrated how the choice of algorithm (weighted/unweighted) can be made based only on the observed network.
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