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Even with the benefits of sustainability and climate change reporting, there is limited information on how municipalities are reporting on performance for external stakeholders in comparison with private sector organizations. The purpose of this research was to gain an understanding of the current state of sustainability and climate change reporting at the local level and to investigate the extent to which municipalities across Ontario, Canada, report. We used content analysis to identify the presence or non-presence of information on the websites of 38 municipalities and analyzed the results using descriptive statistics. Our analysis showed that the sample municipalities were not widely reporting on sustainability or climate change performance. Also, we identified a gap between the number of plans and reports produced by sample municipalities, with the latter being less common, indicating a need for an improved evaluation of plan implementation. Further, we found that a provincial regulation that required municipalities to make their energy conservation and demand management plans public did not guarantee publication of the plan on a municipality’s website. This study contributes to the growing field of sustainability and climate change planning and reporting by local governments and offers empirical evidence specific to Ontario, Canada.

AbstractGold, silver, platinum and palladium typically crystallize with the face-centred cubic structure. Here we report the high-yield solution synthesis of gold nanoribbons in the 4H hexagonal polytype, a previously unreported metastable phase of gold. These gold nanoribbons undergo a phase transition from the original 4H hexagonal to face-centred cubic structure on ligand exchange under ambient conditions. Using monochromated electron energy-loss spectroscopy, the strong infrared plasmon absorption of single 4H gold nanoribbons is observed. Furthermore, the 4H hexagonal phases of silver, palladium and platinum can be readily stabilized through direct epitaxial growth of these metals on the 4H gold nanoribbon surface. Our findings may open up new strategies for the crystal phase-controlled synthesis of advanced noble metal nanomaterials.

Abstract Bitumen is too viscous to be produced by conventional recovery methods and significant amounts are too deep to be recovered by mining, necessitating enhanced in-situ oil recovery techniques. The majority of operating and planned in-situ bitumen projects employ thermal techniques to lower the bitumen's viscosity, allowing it to be produced. The viscosity characteristics of the bitumen consequently have a significant effect on production rates and recovery. Bitumen viscosity and chemical composition variation with depth within a single reservoir column has been reported for many heavy oil and oil sand reservoirs in the Western Canadian Sedimentary Basin and elsewhere in the world. This study investigates, through reservoir simulation, the effects of viscosity variation with depth on the SAGD process and the resulting produced oil characteristics. Oil characteristics, including chemical component and viscosity profiles were built into a variety of reservoir simulation models. The simulation results indicate that the produced oil viscosity and component concentration vary as the steam chamber develops. The trend of the produced oil characteristics is related to the original in-situ profiles of and the reservoir flow barriers. In conjunction with oil rate, surface heave, or other available data, the produced oil characteristics may be used to suggest steam chamber development and the presence of barriers or baffles. The presented approach has potential to become a useful technique for SAGD steam chamber growth monitoring and production optimization.

This study aimed to realize Sustainable Development Goals (SDGs), i.e., no poverty, zero hunger, and sustainable cities and communities through the implementation of an intelligent cattle-monitoring system to enhance dairy production. Livestock industries in developing countries lack the technology that can directly impact meat and dairy products, where human resources are a major factor. This study proposed a novel, cost-effective, smart dairy-monitoring system by implementing intelligent wireless sensor nodes, the Internet of Things (IoT), and a Node-Micro controller Unit (Node-MCU). The proposed system comprises three modules, including an intelligent environmental parameter regularization system, a cow collar (equipped with a temperature sensor, a GPS module to locate the animal, and a stethoscope to update the heart rate), and an automatic water-filling unit for drinking water. Furthermore, a novel IoT-based front end has been developed to take data from prescribed modules and maintain a separate database for further analysis. The presented Wireless Sensor Nodes (WSNs) can intelligently determine the case of any instability in environmental parameters. Moreover, the cow collar is designed to obtain precise values of the temperature, heart rate, and accurate location of the animal. Additionally, auto-notification to the concerned party is a valuable addition developed in the cow collar design. It employed a plug-and-play design to provide ease in implementation. Moreover, automation reduces human intervention, hence labor costs are decreased when a farm has hundreds of animals. The proposed system also increases the production of dairy and meat products by improving animal health via the regularization of the environment and automated food and watering. The current study represents a comprehensive comparative analysis of the proposed implementation with the existing systems that validate the novelty of this work. This implementation can be further stretched for other applications, i.e., smart monitoring of zoo animals and poultry.

The monitoring of a waste separation process in the nuclear power industry is considered. Recent advances in gamma ray emission and electrical impedance tomography mean that it is now feasible to unite these two modalities into a novel dual-modality monitoring method. This paper considers a simple model problem for the identification of a boundary between two distinct waste streams in a semi-continuous rotation separator. The simplicity of the problem affords the opportunity to demonstrate the general feasibility of the approach whilst avoiding unnecessary complications.

Abstract A 500 L biomass fast pyrolysis Auger reactor was designed, constructed and experimented with biomass of Mesquite (Prosopsis juliflora) and rice straw (Oryza sativa). The thermogravimetric analysis of feed stock and the physico chemical properties of the feed and product bio-crude was done as per ASTM standard. An optimization based on Response Surface Methodology was carried out for the operating parameters chosen as: (1) reactor temperature, (2) feedstock-heat carrier ratio and (3) rotational speed of the auger reactor. The optimum bio-crude yield of 42.6 wt.% was observed at 500 °C, feedstock-heat carrier ratio 1:2 and 30 rpm for mesquite sawdust and 34.6 wt.% at 475 °C, 1:2 ratio and 50 rpm for rice straw. Among the two kinds of feedstock tested, the sawdust yielded better product under identical operating conditions. The final bio-crude have properties similar to the results that was reported in the past and has HHV- higher heating value less than petroleum fuel.

This paper proposes a novel consensus-based distributed control algorithm for solving the economic dispatch problem of distributed generators. A legacy central controller can be eliminated in order to avoid a single point of failure, relieve computational burden, maintain data privacy, and support plug-and-play functionalities. The optimal economic dispatch is achieved by allowing the iterative coordination of local agents (consumers and distributed generators). As coordination information, the local estimation of power mismatch is shared among distributed generators through communication networks and does not contain any private information, ultimately contributing to a fair electricity market. Additionally, the proposed distributed algorithm is particularly designed for easy implementation and configuration of a large number of agents in which the distributed decision making can be implemented in a simple proportional-integral (PI) or integral (I) controller. In MATLAB/Simulink simulation, the accuracy of the proposed distributed algorithm is demonstrated in a 29-node system in comparison with the centralized algorithm. Scalability and a fast convergence rate are also demonstrated in a 1400-node case study. Further, the experimental test demonstrates the practical performance of the proposed distributed algorithm using the VOLTTRON platform and a cluster of low-cost credit-card-size single-board PCs. Comment: 16 Pages, 13 figures Figures order and references are corrected!

Coupling between the UEDGE (edge fluid model), GINGRED (grid generation) and CAKE (equilibrium reconstruction) codes opens the door for automated interpretative scrape-off-layer (SOL) analysis over entire discharges, providing information that is essential in efforts to couple the SOL to core transport codes. In this work, we utilize new developments in the autoUEDGE code (Izacard et al. 2018) to investigate the behavior of the DIII-D SOL during the temporal evolution of an edge-localized mode (ELM) cycle. Modeled temperature and density profiles in UEDGE are automatically matched to experimental measurements by iteratively and self-consistently adjusting transport coefficient profiles in the plasma edge. This analysis is completed over multiple ELM cycles of a well-diagnosed discharge with long (∼100ms) inter-ELM periods. Directly after the ELM crash, a short period of high-density, low-temperature conditions is observed in Langmuir probe measurements at the outer divertor. This regime is associated with enhanced Dαemission and incident particle flux, suggesting that the divertor enters a period of high recycling after an ELM crash. After about ∼25ms, divertor conditions return to their pre-ELM conditions and remain there for several tens of milliseconds. Using the autoUEDGE code, the SOL is modeled as a function of ELM cycle using upstream profiles as input. The 2D modeling successfully reproduces both divertor Thomson scattering measurements and the experimentally observed divertor dynamics. Though the recycling is kept fixed throughout the modeling, changes in particle fluxes are consistent with local experimental recycling changes induced by ELMs. Agreement between modeling and observation suggests a strong link between upstream profiles and the high-recycling divertor conditions directly following large type-I ELMs.