The importance of learning for achieving the UK's targets for offshore wind

Using a purpose-built, multi-sectoral energy-economy-environmental model we evaluate the economic and environmental impact of a reduction in the levelized costs of offshore wind energy generation in the UK. Our modelling approach suggests that in order to significantly increase the offshore wind capacity in the UK the required fall in the generation cost should be larger than expected and certainly bigger than that implied by the most recent cost projections developed by the UK Department of Energy and Climate Change (DECC). Potential expansion of the offshore wind sector in the UK crucially depends on the price sensitivity of the energy supply sector and on agent's expectations. Only in our more optimistic scenario do we reach DECC's ambitious challenge of 22 GW offshore wind deployment in 2030 through a constant learning rate alone

Forecasting Petroleum Products Consumption in the Chadian Road Transport Sector using Optimised Grey Models

This study aims to estimate the demand for petroleum products (PP) in the Chadian road sector by 2030 and to determine which of the two models used is the most efficient. The methodology is based on two optimised Grey models, namely: the Sequential-GM(1,N)-GA and NeuralODE-GM(1,1) models.  These models reduce forecasting errors compared with the conventional Grey model. The forecasts confirm that both models are robust, with MAPEs of 1.16% and 2.5% respectively for gasoline and diesel obtained with the Sequential-GM(1,N)-GA, and 3.3% and 4.8% respectively for gasoline and diesel obtained with the NeuralODE-GM(1,1). We note that the Sequential-GM(1,N)-GA is more robust than NeuralODE-GM(1,1) with regard to MAPEs. The estimated consumption needs for gasoline and diesel in the road transport sector by 2030 are 294376818.5 and 381570061.5 litres respectively for the Sequential-GM(1,N)-GA and 264376818.5 and 375570061.5 litres for the NeuralODE-GM(1,1). Based on these results, securing the supply of PP in the road transport sector requires the development of the downstream petroleum sector. The development of alternative energies and the acquisition of hybrid vehicles. A policy encouraging mass transport in urban areas can considerably reduce energy consumption in this sector. This study adds to the literature through the simultaneous use of two new optimised grey models and their comparison in terms of predicting demand for PP in the Chadian road transport sector

The future of road transport

A perfect storm of new technologies and new business models is transforming not only our vehicles, but everything about how we get around, and how we live our lives. The JRC report “The future of road transport - Implications of automated, connected, low-carbon and shared mobility” looks at some main enablers of the transformation of road transport, such as data governance, infrastructures, communication technologies and cybersecurity, and legislation. It discusses the potential impacts on the economy, employment and skills, energy use and emissions, the sustainability of raw materials, democracy, privacy and social fairness, as well as on the urban context. It shows how the massive changes on the horizon represent an opportunity to move towards a transport system that is more efficient, safer, less polluting and more accessible to larger parts of society than the current one centred on car ownership. However, new transport technologies, on their own, won't spontaneously make our lives better without upgrading our transport systems and policies to the 21st century. The improvement of governance and the development of innovative mobility solutions will be crucial to ensure that the future of transport is cleaner and more equitable than its car-centred present.JRC.C.4-Sustainable Transpor

Technological change and sustainable energy policies, modelling exercises for Scotland and the UK

Amid growing environmental concerns, the UK energy sector faces considerable challenges in order to comply with national and regional commitments to decarbonisation. In light of these challenges, the government has implemented a number of policies aimed at ensuring sustainability in the UK energy sector (both in terms of environmental impact and security of supply), while ensuring that the reforms and changes to the sector are achieved at the lowest costs to consumers. Innovation in energy technologies are expected to play a large role in reaching this sustainability objective. The focus of this thesis is to explore the economic and environmental impacts of two UK sustainable energy policies, while considering the role that technological innovation might play in delivering on these objectives. The thesis is divided in two parts; each focusing on the system-wide economic impact of a specific energy policy instrument, in presence of technological change. Part A focuses on the supply side of the electricity sector. It explores the impact of introducing targeted subsidies in a renewable energy sector in Scotland, in presence of endogenous learning-by-doing effects. The literature review highlights the growing awareness in the role of technological change in energy policy. Correspondingly, system-wide energy-economy-environment models used to analyse these policies have increasingly introduced endogenous technological change as a major design feature, whether it is induced through R&D spending or learning effects. Because the latter is the most commonly adopted, it is the focus of the modelling exercise in Part A. A number of alternative specifications of learning-by-doing are identified in the literature and are explored first through micro-simulations. Then, in a CGE model for Scotland, learning-by-doing is introduced in the presence of a production subsidy in the marine energy sector. As the subsidy stimulates the marine electricity generation sector through costs reductions in production, electricity generation from other sources is displaced and the Scottish economy experiences a small expansion. The presence of learning effects is found to accentuate the stimulus from the subsidy. Indeed the costs of marine generation are further reduced as the sector expands.;The choice of assumptions to represent endogenous learning-by-doing is found to matter greatly for the speed and paths of adjustments. In particular, the use of an "economic" functional form (inspired by endogenous growth theory and originating in the top-down modelling literature) to represent learning is favoured in the model, but only when negative returns-to-knowledge are imposed. Part B focuses on the demand side of the energy system and more specifically on households. It examines the economy-wide rebound effects from efficiency gains as a side effect of a one-off energy innovation at UK level: the roll-out of smart electricity meters. First, the household and total rebounds in electricity use in the UK are calculated using an Input-Output model, where reductions in household electricity expenditures are redistributed to other consumption goods. Results show that total rebound is generally smaller than household rebound, reflecting a negative indirect rebound from reductions in the industrial use of electricity. This is due to the relative electricity intensity of electricity compared to other sectors. A disaggregation of the electricity sector into network and generation activities reduces the indirect rebound, and thus the gap in household and total rebound and confirms the strong backwards linkages in electricity activities. The analysis is extended to a CGE model incorporating endogenous prices and incomes. The same efficiency gain is simulated and its system-wide economic and environmental impacts (CO2 emissions) are established. Using findings from the econometric literature on household energy demand, several simulations are conducted to explore rebound effects with alternative consumption structures, where households have different substitution possibilities between electricity and gas. Increased substitution between fuels increases the household electricity rebound (as households substitute more efficient electricity for gas) and in turn total rebound; leading to the extreme case of backfire, but accompanied by the largest CO2 emissions reductions. CGE results persistently show a smaller total rebound than household rebound, (similarly to the IO results) suggesting that the reduction in total UK electricity use could be larger than the reduction in household consumption estimated by the policy-makers, by considering economy-wide effects. Overall, the results of the modelling exercises of this thesis confirm the crucial role of technological change in achieving the goals of sustainability in energy policies, while providing insights on the assumptions for the analysis and modelling of these policies in an economy-wide framework.Amid growing environmental concerns, the UK energy sector faces considerable challenges in order to comply with national and regional commitments to decarbonisation. In light of these challenges, the government has implemented a number of policies aimed at ensuring sustainability in the UK energy sector (both in terms of environmental impact and security of supply), while ensuring that the reforms and changes to the sector are achieved at the lowest costs to consumers. Innovation in energy technologies are expected to play a large role in reaching this sustainability objective. The focus of this thesis is to explore the economic and environmental impacts of two UK sustainable energy policies, while considering the role that technological innovation might play in delivering on these objectives. The thesis is divided in two parts; each focusing on the system-wide economic impact of a specific energy policy instrument, in presence of technological change. Part A focuses on the supply side of the electricity sector. It explores the impact of introducing targeted subsidies in a renewable energy sector in Scotland, in presence of endogenous learning-by-doing effects. The literature review highlights the growing awareness in the role of technological change in energy policy. Correspondingly, system-wide energy-economy-environment models used to analyse these policies have increasingly introduced endogenous technological change as a major design feature, whether it is induced through R&D spending or learning effects. Because the latter is the most commonly adopted, it is the focus of the modelling exercise in Part A. A number of alternative specifications of learning-by-doing are identified in the literature and are explored first through micro-simulations. Then, in a CGE model for Scotland, learning-by-doing is introduced in the presence of a production subsidy in the marine energy sector. As the subsidy stimulates the marine electricity generation sector through costs reductions in production, electricity generation from other sources is displaced and the Scottish economy experiences a small expansion. The presence of learning effects is found to accentuate the stimulus from the subsidy. Indeed the costs of marine generation are further reduced as the sector expands.;The choice of assumptions to represent endogenous learning-by-doing is found to matter greatly for the speed and paths of adjustments. In particular, the use of an "economic" functional form (inspired by endogenous growth theory and originating in the top-down modelling literature) to represent learning is favoured in the model, but only when negative returns-to-knowledge are imposed. Part B focuses on the demand side of the energy system and more specifically on households. It examines the economy-wide rebound effects from efficiency gains as a side effect of a one-off energy innovation at UK level: the roll-out of smart electricity meters. First, the household and total rebounds in electricity use in the UK are calculated using an Input-Output model, where reductions in household electricity expenditures are redistributed to other consumption goods. Results show that total rebound is generally smaller than household rebound, reflecting a negative indirect rebound from reductions in the industrial use of electricity. This is due to the relative electricity intensity of electricity compared to other sectors. A disaggregation of the electricity sector into network and generation activities reduces the indirect rebound, and thus the gap in household and total rebound and confirms the strong backwards linkages in electricity activities. The analysis is extended to a CGE model incorporating endogenous prices and incomes. The same efficiency gain is simulated and its system-wide economic and environmental impacts (CO2 emissions) are established. Using findings from the econometric literature on household energy demand, several simulations are conducted to explore rebound effects with alternative consumption structures, where households have different substitution possibilities between electricity and gas. Increased substitution between fuels increases the household electricity rebound (as households substitute more efficient electricity for gas) and in turn total rebound; leading to the extreme case of backfire, but accompanied by the largest CO2 emissions reductions. CGE results persistently show a smaller total rebound than household rebound, (similarly to the IO results) suggesting that the reduction in total UK electricity use could be larger than the reduction in household consumption estimated by the policy-makers, by considering economy-wide effects. Overall, the results of the modelling exercises of this thesis confirm the crucial role of technological change in achieving the goals of sustainability in energy policies, while providing insights on the assumptions for the analysis and modelling of these policies in an economy-wide framework

The economic and environmental impact of a carbon tax in Scotland : a computable general equilibrium analysis

This paper looks at the economic and environmental impact of a carbon tax in Scotland

Le diagnostic de l'arthrose du membre du cheval

L'arthrose est une pathologie grave, irréversible et sans traitement curatif à l'heure actuelle qui handicape de nombreux chevaux dans leurs activités athlétiques. il est donc important de la détecter au plus tôt. après un rappel anatomique et physiologique de l'organe articulaire, l'auteur fait la synthèse bibliographique des connaissances actuelles sur la pathobiologie de cette affection. enfin, il présente les techniques de diagnostic courantes, nouvelles et expérimentales avec leurs spécificités enfonction des articulations concernées.TOULOUSE-EN Vétérinaire (315552301) / SudocSudocFranceF

The Importance of Learning for Achieving the UK’s Targets for Offshore Wind

Using a purpose-built, multi-sectoral energy-economy-environmental model we evaluate the economic and environmental impact of a reduction in the levelized costs of offshore wind energy generation in the UK. Our modelling approach suggests that in order to significantly increase the offshore wind capacity in the UK the required fall in the generation cost should be larger than expected and certainly bigger than that implied by the most recent cost projections developed by the UK Department of Energy and Climate Change (DECC). Potential expansion of the offshore wind sector in the UK crucially depends on the price sensitivity of the energy supply sector and on agent’s expectations. Only in our more optimistic scenario do we reach DECC’s ambitious challenge of 22 GW offshore wind deployment in 2030 through a constant learning rate alone.JRC.B.3-Territorial Developmen

Disaggregating air, land and maritime transport sectors in the GTAP database

In the Global Trade Analysis Project (GTAP) data base (Aguiar et al., 2019), transport sectors (air, land and maritime) are too aggregated for modelling transport policies for specific modes (aviation/rail/road) and operations (passenger/freight). This limitation is already recognised in the literature, with a number of studies focusing on data quality and transport analysis (e.g., Karkatsoulis et al., 2017, Nuno-Ledesma and Villoria, 2019, Robson et al., 2018). This study splits the air and maritime sectors into two sectors each (air passenger, air freight, water passenger, water freight) and the land transport sectors into four new sectors (road passenger, road freight, rail passenger and rail freight). Our contribution to the literature is an open discussion of the data available paying particular attention to GTAP’s structure, and a step by step procedure on how to split the transport sectors and the data we use. Finally, this paper will discuss baseline projections of the disaggregated transport components. Our methodology to split GTAP database is a simple RAS method, which is used twice (separately for each aggregated sector and each region): first to disaggregate the cost structure of a sector and then to disaggregate its use (sales). We run RAS starting with an already aggregated GTAP database (35 sectors and 49 regions), but the method can be applied to any other dimensions