Estimating Future Costs for Infrastructure in the Proposed Canadian Northern Corridor at Risk From Climate Change

This paper reviews current climate change projections for northern Canada and considers what these mean for infrastructure development in the proposed Canadian Northern Corridor (CNC). We focus on chokepoints along the corridor’s notional route and estimate future costs of infrastructure along the chokepoints. We draw upon climate change projections at the end of the century (2100) using information from several climate variables sourced on the CMIP6 and CMIP5 reports. Climate variables include means and extreme values for temperature, precipitation, wind and their indirect impacts on physical features: permafrost, freezing rain and wildfires. In terms of infrastructure costs, we investigate investment costs and the useful life of nine sectors within transportation, energy and buildings infrastructures. The findings of our analysis show that mean temperatures within the CNC area could increase by 10.9oC, and precipitation by 45 per cent by 2100. Climate change could create chokepoints along the CNC route, affecting key areas essential for transportation flow. Central regions of the corridor are projected to have a higher probability of receiving concomitant impacts on several chokepoints, including combined threats from the increasing frequency of wildfires, freezing rain and permafrost thaw. Adding a climatic layer to investment costs within CNC chokepoints can increase infrastructure costs by more than 101 per cent. Transportation engineering infrastructure, electric power infrastructure and the institutional buildings sectors are most likely to be impacted. Just considering a climate layer to current infrastructure increases costs by more than $12 billion for several hazards such as freezing precipitation (especially Alberta and BC),$7 billion for wildfires (especially BC) and more than $400 million for permafrost (especially Alberta and BC). Infrastructure built along the CNC route will need to be designed to remain functional under different climatic conditions that predominate today. Chokepoints will dictate how buildings and transportation infrastructure should be planned

Estimating Future Costs for Infrastructure in the Proposed Canadian Northern Corridor at Risk From Climate Change

This paper reviews current climate change projections for northern Canada and considers what these mean for infrastructure development in the proposed Canadian Northern Corridor (CNC). We focus on chokepoints along the corridor’s notional route and estimate future costs of infrastructure along the chokepoints. We draw upon climate change projections at the end of the century (2100) using information from several climate variables sourced on the CMIP6 and CMIP5 reports. Climate variables include means and extreme values for temperature, precipitation, wind and their indirect impacts on physical features: permafrost, freezing rain and wildfires. In terms of infrastructure costs, we investigate investment costs and the useful life of nine sectors within transportation, energy and buildings infrastructures. The findings of our analysis show that mean temperatures within the CNC area could increase by 10.9oC, and precipitation by 45 per cent by 2100. Climate change could create chokepoints along the CNC route, affecting key areas essential for transportation flow. Central regions of the corridor are projected to have a higher probability of receiving concomitant impacts on several chokepoints, including combined threats from the increasing frequency of wildfires, freezing rain and permafrost thaw. Adding a climatic layer to investment costs within CNC chokepoints can increase infrastructure costs by more than 101 per cent. Transportation engineering infrastructure, electric power infrastructure and the institutional buildings sectors are most likely to be impacted. Just considering a climate layer to current infrastructure increases costs by more than $12 billion for several hazards such as freezing precipitation (especially Alberta and BC),$7 billion for wildfires (especially BC) and more than $400 million for permafrost (especially Alberta and BC). Infrastructure built along the CNC route will need to be designed to remain functional under different climatic conditions that predominate today. Chokepoints will dictate how buildings and transportation infrastructure should be planned

Effects of stator and rotor core ovality on induction machine behavior

Asymmetries in the air gap of induction motors produce additional harmonics in the flux density and force waves. A complete transient finite element model analyzes the harmonics produced from two possible asymmetries, a stator core ovality and a rotor ovality. The analysis of the air gap flux density and magnetic force waves determined by the finite element model shows unique harmonic frequencies due to the ovality of the air gap

Central Bank Policies and Income and Wealth Inequality:A Survey

This paper reviews recent research on the relationship between central bank policies and inequality. A new paradigm which integrates sticky-prices, incomplete markets, and heterogeneity among households is emerging, which allows for the joint study of how inequality shapes macroeconomic aggregates and how macroeconomic shocks and policies affect inequality. The new paradigm features multiple distributional channels of monetary policy. Most empirical studies, however, analyze each potential channel of redistribution in isolation. Our review suggests that empirical research on the effects of conventional monetary policy on income and wealth inequality yields mixed findings, although there seems to be a consensus that higher inflation, at least above some threshold, increases inequality. In contrast to common wisdom, conclusions concerning the impact of unconventional monetary policies on inequality are also not clear cut. To better understand policy effects on inequality, future research should focus on the estimation of General Equilibrium models with heterogeneous agents

The Effects of \u3cem\u3eTithonia diversifolia\u3c/em\u3e on Dairy Cow Performance

Southeast, South and Central West are the main milk producing regions in the Brazil. Especially in the states of Minas Gerais, Goias and Sao Paulo, the tropical climate is very characteristic, with hot and rainy summers, and dry winters. Dry winters in these states are characterized by scarcity of pasture herbage mass, which directly influence the volume of milk produced. The high volume of milk produced in summer and low volume of milk produced in winter (i.e. seasonality of production which is about 20% of total milk volume) directly affects dairy farmers by reducing its revenue during dry winters due to a drop in milk yield. In addition, it increases the production costs by offering additional roughage supplements to the cattle (sugarcane fresh plus urea, corn silage or sorghum silage), or by feeding more concentrates and/or greater labour costs. Research evaluating the potential of the Tithonia diversifolia in improving milk yield and quality is extremely limited. This research project seeks to develop tools to understand the potential impact on milk composition and cow performance and to evaluate the significance of its outcomes and to aid in the ongoing development of innovative approaches. The aim of this study is to determine the effects of replacing up to 9.1% of sugarcane fresh and up to 6.3% of concentrates (DM basis) with Tithonia diversifolia fresh fed to lactating dairy cows. It is hypothesized that the initial replacement of a portion of the sugarcane fresh and concentrates (corn grain and soybean meal) with the Tithonia diversifolia fresh would not reduce dairy cow performance

Using Machine Learning to Uncover Latent Research Topics in Fishery Models

© 2018 The Author(s). Published with license by Taylor & Francis © 2018, Shaheen Syed and Charlotte Teresa Weber. Modeling has become the most commonly used method in fisheries science, with numerous types of models and approaches available today. The large variety of models and the overwhelming amount of scientific literature published yearly can make it difficult to effectively access and use the output of fisheries modeling publications. In particular, the underlying topic of an article cannot always be detected using keyword searches. As a consequence, identifying the developments and trends within fisheries modeling research can be challenging and time-consuming. This paper utilizes a machine learning algorithm to uncover hidden topics and subtopics from peer-reviewed fisheries modeling publications and identifies temporal trends using 22,236 full-text articles extracted from 13 top-tier fisheries journals from 1990 to 2016. Two modeling topics were discovered: estimation models (a topic that contains the idea of catch, effort, and abundance estimation) and stock assessment models (a topic on the assessment of the current state of a fishery and future projections of fish stock responses and management effects). The underlying modeling subtopics show a change in the research focus of modeling publications over the last 26 years

Eficiência de fungicidas para controle de mofo-branco (Sclerotinia sclerotiorum) em soja, na safra 2015/2016: resultados sumarizados dos ensaios cooperativos.

bitstream/item/148978/1/CT-122.pd