What Should we Expect from Innovation? A Model-Based Assessment of the Environmental and Mitigation Cost Implications of Climate-Related R&D

This paper addresses two basic issues related to technological innovation and climate stabilisation objectives: i) Can innovation policies be effective in stabilising greenhouse gas concentrations? ii) To what extent can innovation policies complement carbon pricing (taxes or permit trading) and improve the economic efficiency of a mitigation policy package? To answer these questions, we use an integrated assessment model with multiple externalities and an endogenous representation of technical progress in the energy sector. We evaluate a range of innovation policies, both as a stand-alone instrument and in combination with other mitigation policies. Even under fairly optimistic assumptions about the funding available for, and the returns to R&D, our analysis indicates that innovation policies alone are unlikely to stabilise global concentration and temperature. The efficiency gains of combining innovation and carbon pricing policies are found to reach about 10% for a stabilisation target of 535 ppm CO2eq. However, such gains are reduced when more plausible (sub-optimal) global innovation policy arrangements are considered.climate change, environmental policy, energy R&D fund, stabilisation costs

A lunar base reference mission for the phased implementation of bioregenerative life support system components

Previous design efforts of a cost effective and reliable regenerative life support system (RLSS) provided the foundation for the characterization of organisms or 'biological processors' in engineering terms and a methodology was developed for their integration into an engineered ecological LSS in order to minimize the mass flow imbalances between consumers and producers. These techniques for the design and the evaluation of bioregenerative LSS have now been integrated into a lunar base reference mission, emphasizing the phased implementation of components of such a BLSS. In parallel, a designers handbook was compiled from knowledge and experience gained during past design projects to aid in the design and planning of future space missions requiring advanced RLSS technologies. The lunar base reference mission addresses in particular the phased implementation and integration of BLS parts and includes the resulting infrastructure burdens and needs such as mass, power, volume, and structural requirements of the LSS. Also, operational aspects such as manpower requirements and the possible need and application of 'robotics' were addressed

An Improved Mathematical Formulation For the Carbon Capture and Storage (CCS) Problem

abstract: Carbon Capture and Storage (CCS) is a climate stabilization strategy that prevents CO2 emissions from entering the atmosphere. Despite its benefits, impactful CCS projects require large investments in infrastructure, which could deter governments from implementing this strategy. In this sense, the development of innovative tools to support large-scale cost-efficient CCS deployment decisions is critical for climate change mitigation. This thesis proposes an improved mathematical formulation for the scalable infrastructure model for CCS (SimCCS), whose main objective is to design a minimum-cost pipe network to capture, transport, and store a target amount of CO2. Model decisions include source, reservoir, and pipe selection, as well as CO2 amounts to capture, store, and transport. By studying the SimCCS optimal solution and the subjacent network topology, new valid inequalities (VI) are proposed to strengthen the existing mathematical formulation. These constraints seek to improve the quality of the linear relaxation solutions in the branch and bound algorithm used to solve SimCCS. Each VI is explained with its intuitive description, mathematical structure and examples of resulting improvements. Further, all VIs are validated by assessing the impact of their elimination from the new formulation. The validated new formulation solves the 72-nodes Alberta problem up to 7 times faster than the original model. The upgraded model reduces the computation time required to solve SimCCS in 72% of randomly generated test instances, solving SimCCS up to 200 times faster. These formulations can be tested and then applied to enhance variants of the SimCCS and general fixed-charge network flow problems. Finally, an experience from testing a Benders decomposition approach for SimCCS is discussed and future scope of probable efficient solution-methods is outlined.Dissertation/ThesisMasters Thesis Industrial Engineering 201

What Should We Expect from Innovation? A Model-Based Assessment of the Environmental and Mitigation Cost Implications of Climate-Related R&D

This paper addresses two basic issues related to technological innovation and climate stabilisation objectives: i) Can innovation policies be effective in stabilising greenhouse gas concentrations? ii) To what extent can innovation policies complement carbon pricing (taxes or permit trading) and improve the economic efficiency of a mitigation policy package? To answer these questions, we use an integrated assessment model with multiple externalities and an endogenous representation of technical progress in the energy sector. We evaluate a range of innovation policies, both as a stand-alone instrument and in combination with other mitigation policies. Even under fairly optimistic assumptions about the funding available for, and the returns to R&D, our analysis indicates that innovation policies alone are unlikely to stabilise global concentration and temperature. The efficiency gains of combining innovation and carbon pricing policies are found to reach about 10% for a stabilisation target of 535 ppm CO2eq. However, such gains are reduced when more plausible (sub-optimal) global innovation policy arrangements are considered.Climate Change, Environmental Policy, Energy R&D Fund, Stabilisation Costs

Optimal design of pipelines network for CO2 transport

Carbon capture and storage (CCS) is widely regarded as an important technical alternative to mitigate CO2 emission. But the planning of the deployment of CCS infrastructure has been a challenging problem, because many constraints have to be considered simultaneously, with a great number of sources and sinks. Moreover, some inevitable nonlinear factors in real-life cases make the design problem even more complex. In this study, an mixed-integer programming (MIP) model for optimal design of pipeline network for CO2 transport in previous studies is retrofitted, and geographical impacts on the pipeline construction cost is incorporated, which is realized on a combined platform of GAMS and ArcGIS. The new model is also applied to a real-life case in Texas to test its performance. The design result shows that the new model is effective and comprehensive for pipeline networks design

Climate cost uncertainty, retrofit cost uncertainty, and infrastructure closedown : a framework for analysis

Large and energy-intensive infrastructure investments with long life times have substantial implications for climate policy. This study focuses on options to scale down energy consumption and carbon emissions now and in the future, and on the costs of doing so. Two ways carbon emissions can be reduced post-investment include retrofitting the infrastructure, or closing it down. Generally, the presence of bulky infrastructure investments makes it more costly to reduce emissions later. Moreover, when expected energy and environmental costs are continually rising, inherent biases in the selection processes for infrastructure investments lead to excessive energy intensity in such investments. Thus great care must be taken when choosing the energy intensity of the infrastructure at the time of investment. Simulations indicate that optimally exercising the retrofit option, when it is available, reduces ex ante expected energy consumption relative to the no-option case. Total energy plus retrofit costs can also be substantially reduced, the more so the larger is ex ante cost uncertainty. However, the availability of the retrofit option also leads to a more energy intensive initial infrastructure choice; this offsets some, but usually not all, of the gains from options for subsequent retrofitting.Energy Production and Transportation,Transport Economics Policy&Planning,Climate Change Mitigation and Green House Gases,Climate Change Economics,Environment and Energy Efficiency

The cost of a future low-carbon electricity system without nuclear power – the case of Sweden

To achieve the goal of deep decarbonization of the electricity system, more and more variable renewable energy (VRE) is being adopted. However, there is no consensus among researchers on whether the goal can be accomplished without large cost escalation if nuclear power is excluded in the future electricity system. In Sweden, where nuclear power generated 41% of the annual electricity supply in 2014, the official goal is 100% renewable electricity production by 2040. Therefore, we investigate the cost of a future low-carbon electricity system without nuclear power for Sweden. We model the European electricity system with a focus on Sweden and run a techno-economic cost optimization model for capacity investment and dispatch of generation, transmission, storage and demand-response, under a CO2 emission constraint of 10 g/kWh. Our results show that there are no, or only minor, cost benefits to reinvest in nuclear power plants in Sweden once the old ones are decommissioned. This holds for a large range of assumptions on technology costs and possibilities for investment in additional transmission capacity. We contrast our results with the recent study that claims severe cost penalties for not allowing nuclear power in Sweden and discuss the implications of methodology choice

Phasing out the U.S. Federal Helium Reserve: Policy insights from a world helium model

This paper develops a detailed partial equilibrium model of the global helium market to study the effects of the recently decided rapid phase out of the U.S. Federal Helium Reserve (FHR), a vast strategic stockpile accumulated during the 1960s. The model incorporates a detailed representation of that industry and treats both helium producers and the FHR as players in a dynamic non-cooperative game. The goal of each player is assumed to be the maximization of discounted profit, subject to technical and resource constraints. We consider two alternative policies aimed at organizing the phase out of the FHR: the currently implemented one and a less stringent one whereby the FHR would be allowed to operate as a profit-maximizing agent during a 20-year extended period. Evidences gained from a series of market simulations indicate that, compared to the current policy, the less stringent policy mandate systematically increases the financial return to the U.S. federal budget, always enhances environmental outcomes as it lowers helium venting into the atmosphere, and also augments global welfare in three out of the four scenarios considered in the paper