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The Social-Ecological Systems (SES) framework serves as a valuable framework to explore and understand social and ecological interactions, and pathways in water governance. Yet, it lacks a robust understanding of change. We argue an analytical and methodological approach to engaging global changes in SES is critical to strengthening the scope and relevance of the SES framework. Relying on SES and resilience thinking, we propose an institutional and cognitive model of change that institutions and natural resources systems co-evolve to provide a dynamic understanding of SES that stands on three causal mechanisms: institutional complexity trap, rigidity trap, and learning processes. We illustrate how Data Cube technology could overcome current limitations and offer reliable avenues to test hypothesis about the dynamics of social-ecological systems and water security by offering to combine spatial and time data with no major technical requirements for users.

The most severe failures in power grids are often characterized as cascading failures where an initial event triggers consequent failures all along the grid often leading to blackouts. Upon identifying a failure and its cascade potential, timely control actions should be performed by the grid operators to mitigate the effect of the cascade. These actions have to be delivered to one or more control devices, creating a dependency between the power grid and its control network. This paper examines the dependency of the operation of the power grid on the control network. Different from literature studies on failure control, our dependency model captures the impact of networking parameters. We formulate an algorithmic model that describes the impact of this dependency on cascade control. Based on this model, we propose an efficient cascade control algorithm using load shedding with consideration of delays in the communication network for power grids. Finally, we evaluate the impact of the power-communication network dependency with uncontrolled grids, ideal/simple control grids and our proposed control scheme. The results demonstrate that the proposed algorithm can significantly reduce the failure of power lines while sustaining larger power demand for users.

AbstractMembrane Technology and Research, Inc. has proposed a hybrid system combining amine scrubbing with membrane technology to reduce energy cost. Previous studies of CO2 absorption mainly focused on coal-fired flue gas with 12% CO2. However, in the hybrid process, the CO2 in the flue gas can be enriched to 20%. Natural gas turbines will have flue gas with as little as 3% CO2。 Based on the arrangement, the hybrid amine/membrane system provides a gas to the system that has double the CO2 concentration of normal flue gas, reduces the volume of gas sent to the capture unit, or reduces the removal requirements for the capture unit.The objective of this work is to minimize the total energy use of stripping concentrated piperazine (PZ) at rich loading when treating flue gas from 3 to 20% inlet CO2. The base-case stripping configuration is the advanced flash stripper with warm rich bypass and cold rich exchanger bypass. . This configuration includes two split cross-exchangers in series, a convective steam heater, a smaller stripper column, a low residence time flash tank, and stripping at high temperature to produce CO2 at 5 to 17bar. Rich loading in 5 and 8m PZ was varied from 0.37 to 0.43mol CO2/mol N. For each rich loading, lean loading was optimized to minimize the total equivalent work. The “Independence” model for PZ in Aspen Plus® was used to simulate the stripping performance.Because 5m PZ has a lower viscosity than 8m PZ, it can achieve a reduced approach temperature in the cross exchanger. The total energy performance for 5m PZ is practically the same as 8m PZ, even though the capacity of 5m PZ is lower. Significantly more energy is required to regenerate solvents with lower rich loading. As CO2 rich loading increases, the equivalent work requirement decreases for the same loading difference between rich and lean.Stripping data for 24 cases, including heat duty, equivalent work, CO2 output pressure, and optimal cold and warm rich bypass were used to build a correlation with CO2 rich and lean loading. The Second Law efficiency based on the ratio of stripping minimum work and total ideal work was introduced to make the most of stripping work. The Second Law efficiency has a maximum value at a specific CO2 loading.

Abstract This study sought to quantify and characterize cassava waste as fuel. The wastes from three cultivars were collected to study and were divided into three distinct parts of the cassava plant: seed stem, thick stalks, and thin stalks. Physical and chemical analyzes were carried out to determine the elemental composition of the waste: volatile matter; fixed carbon; ash; moisture; lignin; cellulose; hemicellulose; ash composition and higher heating value were determined. We conducted a thermogravimetric analysis in oxidizing and inert atmospheres to study the behavior of the waste as fuel. The root productivity obtained ranged from 7.7 to 13.0 t ha−1 yr−1 on a dry basis (db), and the ratio between waste and roots varied from 0.36 to 0.91. The physical and chemical properties of cassava waste are analogous to those of woody biomass regarding the elemental composition, the higher heating value, and thermogravimetric analysis. Ash content varied from 2.5% to 3.5%, reaching around 6.0% in samples unwashed. Approximately 60% of the ashes are alkali oxides, especially P2O5, K2O, and CaO, which have low melting points. The alkali index calculated suggests that there is a strong tendency that the combustion process leads to ash fouling and the formation of ash deposits.

Flexible butyl interconnection segments are synthetically incorporated into an electronically conductive poly(pyrene methacrylate) homopolymer and its copolymer. The insertion of butyl segment makes the pyrene polymer more flexible, and can better accommodate deformation. This new class of flexible and conductive polymers can be used as a polymer binder and adhesive to facilitate the electrochemical performance of a silicon/graphene composite anode material for lithium ion battery application. They act like a “spring” to maintain the electrode mechanical and electrical integrity. High mass loading and high areal capacity, which are critical design requirements of high energy batteries, have been achieved in the electrodes composed of the novel binders and silicon/graphene composite material. A remarkable area capacity of over 5 mAh/cm2 and volumetric capacity of over 1700 Ah/L have been reached at a high current rate of 333 mA/g.

Abstract Microorganisms used in syngas fermentation require nutrients to grow and convert syngas (CO, H2 and CO2) into various products. Many of the essential nutrients can be provided by biochar. Poultry litter biochar (PLBC) contains minerals and trace metals and has a high pH buffering capacity, making it suitable as a nutrient supplement. The effects of PLBC loadings from 1 to 20 g L−1 on syngas fermentation were determined in 250 ml bottle assays. Results showed that 10 and 20 g L−1 PLBC significantly increased ethanol production compared to standard yeast extract (YE) medium. Fermentations in a 3L continuous stirred tank reactor (CSTR) with 10 g L−1 PLBC with and without 4-morpholineethanesulfonic acid (MES) showed 64% and 36% more ethanol production, respectively, than standard medium. The acetic acid accumulated at the beginning of fermentation was completely converted to ethanol in all media tested in the CSTR. These results demonstrate the feasibility of using PLBC medium without costly MES in the CSTR to enhance ethanol production from syngas for potential use at commercial scale.

The rapid development of advanced metering infrastructure provides a new data source—building electrical load profiles with high temporal resolution. Electric load profile characterization can generate useful information to enhance building energy modeling and provide metrics to represent patterns and variability of load profiles. Such characterizations can be used to identify changes to building electricity demand due to operations or faulty equipment and controls. In this study, we proposed a two-path approach to analyze high temporal resolution building electrical load profiles: (1) time-domain analysis and (2) frequency-domain analysis. The commonly adopted time-domain analysis can extract and quantify the distribution of key parameters characterizing load shape such as peak-base load ratio and morning rise time, while a frequency-domain analysis can identify major periodic fluctuations and quantify load variability. We implemented and evaluated both paths using whole-year 15-minute interval smart meter data of 188 commercial office building in Northern California. The results from these two paths are consistent with each other and complementary to represent full dynamics of load profiles. The time- and frequency-domain analyses can be used to enhance building energy modeling by: (1) providing more realistic assumptions about building operation schedules, and (2) validating the simulated electric load profiles using the developed variability metrics against the real building load data.