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Abstract Combining new constraints on future socio‐economic trajectories and the climate system's response to emissions can substantially reduce the projection uncertainty currently clouding regional climate adaptation decisions—more than either constraint individually.
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Cybersecurity practice lags behind cyber technology achievements. Solutions designed to address many problems may and do exist but frequently cannot be broadly deployed due to economic constraints. Whereas security economics focuses on the cost/benefit analysis and supply/demand, we believe that more sophisticated theoretical approaches, such as economic modeling, rarely utilized, would derive greater societal benefits. Unfortunately, today technologists pursuing interesting and elegant solutions have little knowledge of the feasibility for broad deployment of their results and cannot anticipate the influences of other technologies, existing infrastructure, and technology evolution, nor bring the solutions lifecycle into the equation. Additionally, potentially viable solutions are not adopted because the risk perceptions by potential providers and users far outweighs the economic incentives to support introduction/adoption of new best practices and technologies that are not well enough defined. In some cases, there is no alignment with redominant and future business models as well as regulatory and policy requirements. This paper provides an overview of the economics of security, reviewing work that helped to define economic models for the Internet economy from the 1990s. We bring forward examples of potential use of theoretical economics in defining metrics for emerging technology areas, positioning infrastructure investment, and building real-time response capability as part of software development. These diverse examples help us understand the gaps in current research. Filling these gaps will be instrumental for defining viable economic incentives, economic policies, regulations as well as early-stage technology development approaches, that can speed up commercialization and deployment of new technologies in cybersecurity.
Highlights: Black-Right-Pointing-Pointer Life Cycle Assessment is still not fully operational in waste management at local scale. Black-Right-Pointing-Pointer Credibility of WM LCAs is negatively affected by assumptions and lack of transparency. Black-Right-Pointing-Pointer Local technical-social-economic constraints are often not reflected by WM LCAs. Black-Right-Pointing-Pointer A participatory approach can increase acceptability and credibility of WM LCAs. Black-Right-Pointing-Pointer Results of a WM LCA can hardly ever be generalised, thus transparency is essential. - Abstract: The paper summarises the main results obtained from two extensive applications of Life Cycle Assessment (LCA) to the integrated municipal solid waste management systems of Torino and Cuneo Districts in northern Italy. Scenarios with substantial differences in terms of amount of waste, percentage of separate collection and options for the disposal of residual waste are used to discuss the credibility and acceptability of the LCA results, which are adversely affected by the large influence of methodological assumptions and the local socio-economic constraints. The use of site-specific data on full scale waste treatment facilities and the adoption of a participatory approach for the definition of the most sensible LCA assumptions are used to assist local public administrators and stakeholders showing them that LCA can be operational to waste management at local scale.
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Stabilizing the global climate will require large-scale global deployment of low-carbon technologies. Even in the presence of aggressive climate policies, however, the diffusion of such technologies may be limited by several, institutional, behavioral, and social factors. In this paper, we review the literature on the sources of such diffusion constraints, and explore the potential implications of such non-economic constraints based on the GCAM integrated assessment model. Our analysis highlights that non-economic factors that limit technology deployment may have sizeable impacts on the feasibility and mitigation costs of achieving stringent stabilization targets. And such impacts are greatly amplified with major delays in serious climate policies. The results generally indicate that constraints on the expansions of CCS and renewables are more costly than those on nuclear or bioenergy, and jointly constraining these technologies leaves some scenarios infeasible.
In this final report describes and documents research that was conducted by the Ecological Engineering Research Program (EERP) at the University of the Pacific (Stockton, CA) under subcontract to Fiscalini Farms LP for work under the Assistance Agreement DE-EE0001895 'Measurement and Evaluation of a Dairy Anaerobic Digestion/Power Generation System' from the United States Department of Energy, National Energy Technology Laboratory. Fiscalini Farms is operating a 710 kW biomass-energy power plant that uses bio-methane, generated from plant biomass, cheese whey, and cattle manure via mesophilic anaerobic digestion, to produce electricity using an internal combustion engine. The primary objectives of the project were to document baseline conditions for the anaerobic digester and the combined heat and power (CHP) system used for the dairy-based biomass-energy production. The baseline condition of the plant was evaluated in the context of regulatory and economic constraints. In this final report, the operation of the plant between start-up in 2009 and operation in 2010 are documented and an interpretation of the technical data is provided. An economic analysis of the biomass energy system was previously completed (Appendix A) and the results from that study are discussed briefly in this report. Results from the start-up and first year of operation indicate that mesophilic anaerobic digestion of agricultural biomass, combined with an internal combustion engine, is a reliable source of alternative electrical production. A major advantage of biomass energy facilities located on dairy farms appears to be their inherent stability and ability to produce a consistent, 24 hour supply of electricity. However, technical analysis indicated that the Fiscalini Farms system was operating below capacity and that economic sustainability would be improved by increasing loading of feedstocks to the digester. Additional operational modifications, such as increased utilization of waste heat and better documentation of potential of carbon credits, would also improve the economic outlook. Analysis of baseline operational conditions indicated that a reduction in methane emissions and other greenhouse gas savings resulted from implementation of the project. The project results indicate that using anaerobic digestion to produce bio-methane from agricultural biomass is a promising source of electricity, but that significant challenges need to be addressed before dairy-based biomass energy production can be fully integrated into an alternative energy economy. The biomass energy facility was found to be operating undercapacity. Economic analysis indicated a positive economic sustainability, even at the reduced power production levels demonstrated during the baseline period. However, increasing methane generation capacity (via the importation of biomass codigestate) will be critical for increasing electricity output and improving the long-term economic sustainability of the operation. Dairy-based biomass energy plants are operating under strict environmental regulations applicable to both power-production and confined animal facilities and novel approached are being applied to maintain minimal environmental impacts. The use of selective catalytic reduction (SCR) for nitrous oxide control and a biological hydrogen sulfide control system were tested at this facility. Results from this study suggest that biomass energy systems can be compliant with reasonable scientifically based air and water pollution control regulations. The most significant challenge for the development of biomass energy as a viable component of power production on a regional scale is likely to be the availability of energy-rich organic feedstocks. Additionally, there needs to be further development of regional expertise in digester and power plant operations. At the Fiscalini facility, power production was limited by the availability of biomass for methane generation, not the designed system capacity. During the baseline study period, feedstocks included manure, sudan grass silage, and refused-feed. The ability of the dairy to produce silage in excess of on-site feed requirements limited power production. The availability of biomass energy crops and alternative feedstocks, such as agricultural and food wastes, will be a major determinant to the economic and environmental sustainability of biomass based electricity production.
Brassica carinata or Ethiopian mustard, a non-edible oilseed brassica, is a low carbon, purpose-grown, and none-to-low indirect land-use change bioenergy feedstock for the production of drop-in sustainable aviation fuel, biodiesel, renewable diesel, and a suite of value-added coproducts. Carinata oil converted to drop-in fuel using an American Society for Testing and Materials approved Catalytic Hydrothermolysis process has been successfully tested in commercial and military aviation. Carinata meal, the residue after oil extraction, is a high-protein feed supplement for livestock, poultry, and swine, and can also yield specialty products. The Southeast Partnership for Advanced Renewables from Carinata (SPARC) is a public–private partnership formed with a twofold mission: (1) Removing physical, environmental, social, and economic constraints that prevent regional intensification of carinata production as a low-carbon feedstock for renewable fuel and coproducts and (2) demonstrating enhanced value across the entire value chain by mitigating risk to farmers and other stakeholders. The partnership's goal is to energize the US bioeconomy through sustainable agriculture and thus contribute to energy security and economic diversification. SPARC relies on a combination of cutting-edge multidisciplinary research and active industry engagement to facilitate adoption of the crop. This involves informing stakeholders along the entire supply chain, from producers to end-users, policymakers, influencers, and the public, about the opportunities and best practices related to carinata. This article provides context and background concerning carinata commercialization as a winter cash crop in the Southeast US for renewable fuels and bioproducts. The advances made to date in the areas of feedstock development, fuel and coproduct development, meal valorization, supply chain logistics, and stakeholder engagement are outlined.
The Biomass Scenario Model (BSM) is a unique, carefully validated, state-of-the-art fourth-generation model of the domestic bioenergy supply chain which explicitly focuses on policy issues and their potential side effects. It integrates resource availability, behavior, policy, and physical, technological, and economic constraints. The BSM uses system-dynamics simulation to model dynamic interactions across the supply chain; it tracks the deployment of biofuels given technological development and the reaction of the investment community to those technologies in the context of land availability, the competing oil market, consumer demand for biofuels, and government policies over time. It places a strong emphasis on the behavior and decision-making of various economic agents. The model treats the major infrastructure-compatible fuels. Scenario analysis based on the BSM shows that the biofuels industry tends not to rapidly thrive without significant external actions in the early years of its evolution. An initial focus for jumpstarting the industry typically has strongest results in the BSM in areas where effects of intervention have been identified to be multiplicative. In general, we find that policies which are coordinated across the whole supply chain have significant impact in fostering the growth of the biofuels industry and that the production of tens of billions of gallons of biofuels may occur under sufficiently favorable conditions.
The Biomass Scenario Model (BSM) is an important tool for exploring vibrant future bioeconomy scenarios that leverage domestic resources. Developed by NREL and BETO, this model of the domestic biofuels supply chain has been used to explore success strategies for BETO's activities towards bioeconomy growth. The BSM offers a robust test bed for detailed exploration of effects of BETO activities within the complex context of resource availability; physical, technological, and economic constraints; behavior; and policy. The public release of the model in 2017 will allow broad engagement with the theme of the conference as model users can analyze bioeconomy growth, domestic biomass resource use, and associated effects. The BSM is a carefully validated, state-of-the-art, dynamic model of the biomass to biofuels supply chain. Using a system dynamics simulation modeling approach, the model tracks long-term deployment of biofuels given technology development and investment, considering land availability, the competing oil market, consumer demand, and government policies over time. Sample outputs include biofuels production, feedstock use, capital investment, incentives, and costs of feedstocks and fuels. BSM scenarios reveal technological, economic, and policy challenges, as well as opportunities for dynamic growth of the bioeconomy with strategic public and private investment at key points in the system. The model logic and results have been reviewed extensively, through collaborative analysis, expert reviews and external publications (https://www.zotero.org/groups/bsm_publications/).
The production of biodiesel has notably increased over the past decade. Currently, plant oil is the main feedstock for biodiesel production, but, due to concerns related to the competition with food production, alternative oil feedstocks have to be found. Oleaginous yeasts are known to produce high amounts of lipids, but no integrated process from microbial fermentation to final biodiesel production has reached commercial realization yet due to economic constraints. Therefore, growth and lipid production of red yeast Rhodotorula glutinis was tested on low-cost substrates, namely, wastewaters from potato, fruit juice, and lettuce processing. Additionally, the production of carotenoids as high-value by-products was examined. All evaluated wastewaters met the general criteria for microbial lipid production. However, no significant increase in lipid content was observed, probably due to lack of available carbon in wastewaters from fruit juice and lettuce processing, and excess of available nitrogen in potato processing wastewater, respectively. During growth on wastewaters from fruit juice and lettuce processing the carotenoid content increased significantly in the first 48 hours. The relations between carbon content, nitrogen content, and carotenoid production need to be further assessed. For economic viability, lipid and carotenoid production needs to be increased significantly. Lastly, the screening of feedstocks should be extended to other wastewaters.
Abstract Accurate knowledge of the mechanical loads of wind turbine gearboxes has become essential in modern, highly loaded gearbox designs, as maintaining or even improving gearbox reliability with increasing torque density demands is proving to be challenging. Unfortunately, the traditional method of measuring dynamic mechanical torque using strain gauges placed on the outer surface of a rotating shaft and transmitting the resulting signal is unsuitable for serial deployment due to technical and economic constraints. An alternative method based on fiber-optic strain sensors placed on the stationary outer surface of the gearbox ring gear has been proposed. Like shaft torsion, the radial deformation of the ring gear is proportionate to the rotor torque. Placing the sensors on a stationary component is a cost-effective alternative for serial implementation because the need for complex and expensive data transfer via wireless transmission or a slip ring is eliminated. In this paper, we present the results of an extensive field experiment conducted to evaluate the torque measurement accuracy of this novel sensing solution installed on the gearbox of a Gamesa G97 2-MW wind turbine at the National Renewable Energy Laboratory’s Flatirons Campus. Torque measurements derived from fiber-optic strain sensors placed on the ring gear of the planetary stage are compared to conventional torque measurements from strain gauges placed on the main shaft. Two different torque estimation data processing methods were evaluated, with the method based on operational deflection shapes providing the most accurate results with an average normalized root mean square error below 0.7% for a load revolution distribution analysis. The effect of operating conditions on the torque estimate was also investigated, and the third planet-passing operational deflection shape was found to be the least sensitive to nontorque load-related effects. The fiber-optic strain sensors’ successful operation during the complete test campaign has demonstrated a robust and accurate solution for fleet-wide enhanced gearbox remaining useful life estimation.
Carbon dioxide (CO 2 ) generated by fossil fuel combustion can have serious consequences for humans and environments. Carbon capture, utilization and geological storage (CCUS) is a key approach to reduce the emissions of the anthropogenic CO 2 into the atmosphere. Of those, sequestering the CO 2 into depleted hydrocarbon reservoirs with associated enhanced oil recovery is the most achievable approach under current economic constraints since it increases recovery of existing oil reserves, and bridges the gap between nonprofit geological CO 2 sequestration and profit CO 2 -EOR. The Upper Devonian fluvial sandstone reservoir in Jacksonburg-Stringtown oil field in West Virginia, which has produced over 22 million barrels of oil since 1895, is an ideal candidate for CO 2 sequestration coupled with EOR. This research illustrates an example of CCUS, in which CO 2 is sequestered into underground meanwhile enhanced oil recovery from the depleted hydrocarbon reservoir by water alternating gas (WAG) strategy. Three CO 2 storage mechanisms including structural/stratigraphic trapping, dissolution trapping, and residual trapping are considered. A 3D geological model is constructed based on existing geological data from the Jacksonburg-Stringtown oil field. A 3D composition fluid model with 0.4 pore volume (PV) of water injection before WAG process is considered as a benchmark of this study. Several factors including WAG cycle period, injection time ratio, CO 2 injection rate are evaluated. After injection wells are completely shut-in, stored CO 2 is monitored for additional 200 years as a function of various storage mechanisms. The result shows that over 6 years of WAG injection, total 12 - 40 MMlb-mol CO 2 is sequestrated and oil recovery factor can achieve 28%. As a conclusion, this research constructs a basic workflow for CO 2 storage coupled with CO 2 -EOR which can be applied to other super-mature oil fields.
Alaska is an expansive region known for its abundant natural resources, including thousands of miles of streams and rivers. These rivers represent potential opportunities for future hydropower development that could provide reliable energy supply for local communities. There is limited long-term high temporal resolution streamflow data available for the region, making data-driven estimates of potential hydropower and its variability across the state challenging. This study provides a novel data-driven approach for hydropower capacity estimation across Alaska. We use supervised machine learning to develop a relationship between the daily and peak flow duration curves in order to augment the size of our dataset from 44 sites to 67 sites. We perform a stochastic hydropower estimation across the 67 sites and identify approximately 1000 MW of total potential hydropower capacity distributed across these sites. Our study provides the first step towards more comprehensive hydropower estimation for this critical region, highlighting the need for future work integrating high-resolution spatial data, community needs, and economic constraints in estimates of potential hydropower development in Alaska.
Iron electrocoagulation (Fe-EC) has been shown to effectively remove arsenic from contaminated groundwater at low cost and has the potential to improve access to safe drinking water for millions of people. Understanding how operating conditions, such as the Fe dosage rate and the O 2 recharge rate, affect arsenic removal at different pH values is crucial to maximize the performance of Fe-EC under economic constraints. In this work, we improved upon an existing computational model to investigate the combined effects of pH, Fe dosage rate, and O 2 recharge rate on arsenic removal in Fe-EC. We showed that the impact of the Fe dosage rate strongly depends on pH and on the O 2 recharge rate, which has important practical implications. We identified the process limiting arsenic removal (As(III) oxidation versus As(V) adsorption) at different pH values, which allowed us to interpret the effect of operating conditions on Fe-EC performance. Finally, we assessed the robustness of the trends predicted by the model, which assumes a constant pH, against lab experiments reproducing more realistic conditions where pH is allowed to drift during treatment as a result of equilibration with atmospheric CO 2 . Furthermore, our results provide a nuanced understanding of how operating conditions impact arsenic removal by Fe-EC and can inform decisions regarding the operation of this technology in a range of groundwaters.
A key feature of neutron based interrogation systems is the need for adequate provision of shielding around the facility. Accelerator facilities adapted for fast neutron generation are not necessarily suitably equipped to ensure complete containment of the vast quantity of neutrons generated, typically >10{sup 11} n{center_dot}s{sup -1}. Simulating the neutron leakage from a facility is not a simple exercise since the energy and directional distribution can only be approximated. Although adequate horizontal, planar shielding provision is made for a neutron generator facility, it is sometimes the case that vertical shielding is minimized, due to structural and economic constraints. It is further justified by assuming the atmosphere above a facility functions as an adequate radiation shield. It has become apparent that multiple neutron scattering within the atmosphere can result in a measurable dose of neutrons reaching ground level some distance from a facility, an effect commonly known as skyshine. This paper describes a neutron detection system developed to monitor neutrons detected several hundred metres from a neutron source due to the effect of skyshine.