Coral energy reserves and calcification in a high-CO2 world at two temperatures

Rising atmospheric CO2 concentrations threaten coral reefs globally by causing ocean acidification (OA) and warming. Yet, the combined effects of elevated pCO2 and temperature on coral physiology and resilience remain poorly understood. While coral calcification and energy reserves are important health indicators, no studies to date have measured energy reserve pools (i.e., lipid, protein, and carbohydrate) together with calcification under OA conditions under different temperature scenarios. Four coral species, Acropora millepora, Montipora monasteriata, Pocillopora damicornis, Turbinaria reniformis, were reared under a total of six conditions for 3.5 weeks, representing three pCO2 levels (382, 607, 741 µatm), and two temperature regimes (26.5, 29.0°C) within each pCO2 level. After one month under experimental conditions, only A. millepora decreased calcification (-53%) in response to seawater pCO2 expected by the end of this century, whereas the other three species maintained calcification rates even when both pCO2 and temperature were elevated. Coral energy reserves showed mixed responses to elevated pCO2 and temperature, and were either unaffected or displayed nonlinear responses with both the lowest and highest concentrations often observed at the mid-pCO2 level of 607 µatm. Biweekly feeding may have helped corals maintain calcification rates and energy reserves under these conditions. Temperature often modulated the response of many aspects of coral physiology to OA, and both mitigated and worsened pCO2 effects. This demonstrates for the first time that coral energy reserves are generally not metabolized to sustain calcification under OA, which has important implications for coral health and bleaching resilience in a high-CO2 world. Overall, these findings suggest that some corals could be more resistant to simultaneously warming and acidifying oceans than previously expected.

Differential impacts of elevated CO2 and acidosis on the energy budget of gill and liver cells from Atlantic cod

Ocean acidification impacts fish and other marine species through increased seawater PCO2 levels (hypercapnia). Knowledge of the physiological mechanisms mediating effects in various tissues of fish is incomplete. Here we tested the effects of extracellular hypercapnia and acidosis on energy metabolism of gill and liver cells of Atlantic cod. Exposure media mimicked blood conditions in vivo, either during normo- or hypercapnia and at control or acidic extracellular pH (pHe). We determined metabolic rate and energy expenditure for protein biosynthesis, Na+/K+-ATPase and H+-ATPase and considered nutrition status by measurements of metabolic rate and protein biosynthesis in media with and without free amino acids (FAA). Addition of FAA stimulated hepatic but not branchial oxygen consumption. Normo- and hypercapnic acidosis as well as hypercapnia at control pHe depressed metabolic stimulation of hepatocytes. In gill cells, acidosis depressed respiration independent of PCO2 and FAA levels. For both cell types, depressed respiration was not correlated with the same reduction in energy allocated to protein biosynthesis or Na+/K+-ATPase. Hepatic energy expenditure for protein synthesis and Na+/K+- ATPase was even elevated at acidic compared to control pHe suggesting increased costs for ion regulation and cel- lular reorganization. Hypercapnia at control pHe strongly reduced oxygen demand of branchial Na+/K+-ATPase with a similar trend for H+-ATPase. We conclude that extracellular acidosis triggers metabolic depression in gill and metabolically stimulated liver cells. Additionally, hypercapnia itself seems to limit capacities for metabolic usage of amino acids in liver cells while it decreases the use and costs of ion regulatory ATPases in gill cells.

Seawater carbonate chemistry and energy status in the periwinkle Littorina littorea during experiments, 2011

In the future, marine organisms will face the challenge of coping with multiple environmental changes associated with increased levels of atmospheric Pco2, such as ocean warming and acidification. To predict how organisms may or may not meet these challenges, an in-depth understanding of the physiological and biochemical mechanisms underpinning organismal responses to climate change is needed. Here, we investigate the effects of elevated Pco2 and temperature on the whole-organism and cellular physiology of the periwinkle Littorina littorea. Metabolic rates (measured as respiration rates), adenylate energy nucleotide concentrations and indexes, and end-product metabolite concentrations were measured. Compared with values for control conditions, snails decreased their respiration rate by 31% in response to elevated Pco2 and by 15% in response to a combination of increased Pco2 and temperature. Decreased respiration rates were associated with metabolic reduction and an increase in end-product metabolites in acidified treatments, indicating an increased reliance on anaerobic metabolism. There was also an interactive effect of elevated Pco2 and temperature on total adenylate nucleotides, which was apparently compensated for by the maintenance of adenylate energy charge via AMP deaminase activity. Our findings suggest that marine intertidal organisms are likely to exhibit complex physiological responses to future environmental drivers, with likely negative effects on growth, population dynamics, and, ultimately, ecosystem processes.

Impacts of seawater acidification on mantle gene expression patterns of the Baltic Sea blue mussel: implications for shell formation and energy metabolism, link to supplementary material

Marine organisms have to cope with increasing CO2 partial pressures and decreasing pH in the oceans. We elucidated the impacts of an 8-week acclimation period to four seawater pCO2 treatments (39, 113, 243 and 405 Pa/385, 1,120, 2,400 and 4,000 µatm) on mantle gene expression patterns in the blue mussel Mytilus edulis from the Baltic Sea. Based on the M. edulis mantle tissue transcriptome, the expression of several genes involved in metabolism, calcification and stress responses was assessed in the outer (marginal and pallial zone) and the inner mantle tissues (central zone) using quantitative real-time PCR. The expression of genes involved in energy and protein metabolism (F-ATPase, hexokinase and elongation factor alpha) was strongly affected by acclimation to moderately elevated CO2 partial pressures. Expression of a chitinase, potentially important for the calcification process, was strongly depressed (maximum ninefold), correlating with a linear decrease in shell growth observed in the experimental animals. Interestingly, shell matrix protein candidate genes were less affected by CO2 in both tissues. A compensatory process toward enhanced shell protection is indicated by a massive increase in the expression of tyrosinase, a gene involved in periostracum formation (maximum 220-fold). Using correlation matrices and a force-directed layout network graph, we were able to uncover possible underlying regulatory networks and the connections between different pathways, thereby providing a molecular basis of observed changes in animal physiology in response to ocean acidification.

A new method for resolving uncertainty of energy requirements in large water breathers: the ‘mega-flume’ seagoing swim-tunnel respirometer

Body size is a key determinant of metabolic rate, but logistical constraints have led to a paucity of energetics measurements from large water-breathing animals. As a result, estimating energy requirements of large fish generally relies on extrapolation of metabolic rate from individuals of lower body mass using allometric relationships that are notoriously variable. Swim-tunnel respirometry is the ‘gold standard’ for measuring active metabolic rates in water-breathing animals, yet previous data are entirely derived from body masses <10 kg – at least one order of magnitude lower than the body masses of many top-order marine predators. Here, we describe the design and testing of a new method for measuring metabolic rates of large water-breathing animals: a c. 26 000 L seagoing ‘mega-flume’ swim-tunnel respirometer. We measured the swimming metabolic rate of a 2·1-m, 36-kg zebra shark Stegostoma fasciatum within this new mega-flume and compared the results to data we collected from other S. fasciatum (3·8–47·7 kg body mass) swimming in static respirometers and previously published measurements of active metabolic rate measurements from other shark species. The mega-flume performed well during initial tests, with intra- and interspecific comparisons suggesting accurate metabolic rate measurements can be obtained with this new tool. Inclusion of our data showed that the scaling exponent of active metabolic rate with mass for sharks ranging from 0·13 to 47·7 kg was 0·79; a similar value to previous estimates for resting metabolic rates in smaller fishes. We describe the operation and usefulness of this new method in the context of our current uncertainties surrounding energy requirements of large water-breathing animals. We also highlight the sensitivity of mass-extrapolated energetic estimates in large aquatic animals and discuss the consequences for predicting ecosystem impacts such as trophic cascades.

A new method for resolving uncertainty of energy requirements in large water breathers: the ‘mega-flume’ seagoing swim-tunnel respirometer

Body size is a key determinant of metabolic rate, but logistical constraints have led to a paucity of energetics measurements from large water-breathing animals. As a result, estimating energy requirements of large fish generally relies on extrapolation of metabolic rate from individuals of lower body mass using allometric relationships that are notoriously variable. Swim-tunnel respirometry is the ‘gold standard’ for measuring active metabolic rates in water-breathing animals, yet previous data are entirely derived from body masses <10 kg – at least one order of magnitude lower than the body masses of many top-order marine predators. Here, we describe the design and testing of a new method for measuring metabolic rates of large water-breathing animals: a c. 26 000 L seagoing ‘mega-flume’ swim-tunnel respirometer. We measured the swimming metabolic rate of a 2·1-m, 36-kg zebra shark Stegostoma fasciatum within this new mega-flume and compared the results to data we collected from other S. fasciatum (3·8–47·7 kg body mass) swimming in static respirometers and previously published measurements of active metabolic rate measurements from other shark species. The mega-flume performed well during initial tests, with intra- and interspecific comparisons suggesting accurate metabolic rate measurements can be obtained with this new tool. Inclusion of our data showed that the scaling exponent of active metabolic rate with mass for sharks ranging from 0·13 to 47·7 kg was 0·79; a similar value to previous estimates for resting metabolic rates in smaller fishes. We describe the operation and usefulness of this new method in the context of our current uncertainties surrounding energy requirements of large water-breathing animals. We also highlight the sensitivity of mass-extrapolated energetic estimates in large aquatic animals and discuss the consequences for predicting ecosystem impacts such as trophic cascades.

Optimal day-ahead scheduling of integrated urban energy systems

An optimal day-ahead scheduling method (ODSM) for the integrated urban energy system (IUES) is introduced, which considers the reconfigurable capability of an electric distribution network. The hourly topology of a distribution network, a natural gas network, the energy centers including the combined heat and power (CHP) units, different energy conversion devices and demand responsive loads (DRLs), are optimized to minimize the day-ahead operation cost of the IUES. The hourly reconfigurable capability of the electric distribution network utilizing remotely controlled switches (RCSs) is explored and discussed. The operational constraints from the unbalanced three-phase electric distribution network, the natural gas network, and the energy centers are considered. The interactions between the electric distribution network and the natural gas network take place through conversion of energy among different energy vectors in the energy centers. An energy conversion analysis model for the energy center was developed based on the energy hub model. A hybrid optimization method based on genetic algorithm (GA) and a nonlinear interior point method (IPM) is utilized to solve the ODSM model. Numerical studies demonstrate that the proposed ODSM is able to provide the IUES with an effective and economical day-ahead scheduling scheme and reduce the operational cost of the IUES.

Benchmarking Energy Transitions: An Irish Case Study

The challenges of a low carbon energy transition have now been recognized by most nation states, each of whom have responded with differing visions, strategies and programmes, with variable veracity and effectiveness. Given the complexity of each country’s energy system (and sub-systems such as mobility, food etc), the differing sources and wealth of indigenous energy resources, the variable legacy of the fossil fuel regime and differing capacity to respond to global shifts in energy markets, it is clear that each country will respond to this challenge in very different ways.
This poses difficulties for understanding the extent to which a transition may be taking hold in any territory as simple indicators such as GHG emission data or increases in renewable energy ignore the complex contexts in which transitions take place. Drawing on the results of a study, funded by the Irish Environmental Protection Agency (Characterizing and Catalyzing Transitions) and using the wider theoretical framework of socio-technological transitions, this paper will explore the challenges, virtues and constraints of attempting to ‘benchmark’ the Republic of Ireland’s transition. This will lead to wider observations on the normative nature of benchmarking and a critical review of how we conceptualize the very idea of transition.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Optimized operations of Distributed Renewable Energy Sources in Smart Grid

The renewable energy sources (RES) will play a vital role in the future power needs in view of the increasing demand of electrical energy and depletion of fossil fuel with its environmental impact. The main constraints of renewable energy (RE) generation are high capital investment, fluctuation in generation and requirement of vast land area. Distributed RE generation on roof top of buildings will overcome these issues to some extent. Any system will be feasible only if it is economically viable and reliable. Economic viability depends on the availability of RE and requirement of energy in specific locations. This work is directed to examine the economic viability of the system at desired location and demand.

Energy Cooperation in Energy Harvesting Communication Systems

In energy harvesting communications, users transmit messages using energy harvested from nature. In such systems, transmission policies of the users need to be carefully designed according to the energy arrival profiles. When the energy management policies are optimized, the resulting performance of the system depends only on the energy arrival profiles. In this dissertation, we introduce and analyze the notion of energy cooperation in energy harvesting communications where users can share a portion of their harvested energy with the other users via wireless energy transfer. This energy cooperation enables us to control and optimize the energy arrivals at users to the extent possible. In the classical setting of cooperation, users help each other in the transmission of their data by exploiting the broadcast nature of wireless communications and the resulting overheard information. In contrast to the usual notion of cooperation, which is at the signal level, energy cooperation we introduce here is at the battery energy level. In a multi-user setting, energy may be abundant in one user in which case the loss incurred by transferring it to another user may be less than the gain it yields for the other user. It is this cooperation that we explore in this dissertation for several multi-user scenarios, where energy can be transferred from one user to another through a separate wireless energy transfer unit. We first consider the offline optimal energy management problem for several basic multi-user network structures with energy harvesting transmitters and one-way wireless energy transfer. In energy harvesting transmitters, energy arrivals in time impose energy causality constraints on the transmission policies of the users. In the presence of wireless energy transfer, energy causality constraints take a new form: energy can flow in time from the past to the future for each user, and from one user to the other at each time. This requires a careful joint management of energy flow in two separate dimensions, and different management policies are required depending on how users share the common wireless medium and interact over it. In this context, we analyze several basic multi-user energy harvesting network structures with wireless energy transfer. To capture the main trade-offs and insights that arise due to wireless energy transfer, we focus our attention on simple two- and three-user communication systems, such as the relay channel, multiple access channel and the two-way channel. Next, we focus on the delay minimization problem for networks. We consider a general network topology of energy harvesting and energy cooperating nodes. Each node harvests energy from nature and all nodes may share a portion of their harvested energies with neighboring nodes through energy cooperation. We consider the joint data routing and capacity assignment problem for this setting under fixed data and energy routing topologies. We determine the joint routing of energy and data in a general multi-user scenario with data and energy transfer. Next, we consider the cooperative energy harvesting diamond channel, where the source and two relays harvest energy from nature and the physical layer is modeled as a concatenation of a broadcast and a multiple access channel. Since the broadcast channel is degraded, one of the relays has the message of the other relay. Therefore, the multiple access channel is an extended multiple access channel with common data. We determine the optimum power and rate allocation policies of the users in order to maximize the end-to-end throughput of this system. Finally, we consider the two-user cooperative multiple access channel with energy harvesting users. The users cooperate at the physical layer (data cooperation) by establishing common messages through overheard signals and then cooperatively sending them. For this channel model, we investigate the effect of intermittent data arrivals to the users. We find the optimal offline transmit power and rate allocation policy that maximize the departure region. When the users can further cooperate at the battery level (energy cooperation), we find the jointly optimal offline transmit power and rate allocation policy together with the energy transfer policy that maximize the departure region.

Selection of optimal operating conditions based on minimum energy consumption for an acrylonitrile recovery unit

The selection of the optimal operating conditions for an industrial acrylonitrile recovery unit was conducted by the systematic application of the response surface methodology, based on the minimum energy consumption and products specifications as process constraints. Unit models and plant simulation were validated against operating data and information. A sensitivity analysis was carried out in order to identify the set of parameters that strongly affect the trajectories of the system while keeping products specifications. The results suggest that energy savings of up to 10% are possible by systematically adjusting operating conditions.

JOINT ENERGY BEAMFORMING AND TIME ASSIGNMENT FOR COOPERATIVE WIRELESS POWERED NETWORKS

Wireless power transfer (WPT) and radio frequency (RF)-based energy har- vesting arouses a new wireless network paradigm termed as wireless powered com- munication network (WPCN), where some energy-constrained nodes are enabled to harvest energy from the RF signals transferred by other energy-sufficient nodes to support the communication operations in the network, which brings a promising approach for future energy-constrained wireless network design. In this paper, we focus on the optimal WPCN design. We consider a net- work composed of two communication groups, where the first group has sufficient power supply but no available bandwidth, and the second group has licensed band- width but very limited power to perform required information transmission. For such a system, we introduce the power and bandwidth cooperation between the two groups so that both group can accomplish their expected information delivering tasks. Multiple antennas are employed at the hybrid access point (H-AP) to en- hance both energy and information transfer efficiency and the cooperative relaying is employed to help the power-limited group to enhance its information transmission throughput. Compared with existing works, cooperative relaying, time assignment, power allocation, and energy beamforming are jointly designed in a single system. Firstly, we propose a cooperative transmission protocol for the considered system, where group 1 transmits some power to group 2 to help group 2 with information transmission and then group 2 gives some bandwidth to group 1 in return. Sec- ondly, to explore the information transmission performance limit of the system, we formulate two optimization problems to maximize the system weighted sum rate by jointly optimizing the time assignment, power allocation, and energy beamforming under two different power constraints, i.e., the fixed power constraint and the aver- age power constraint, respectively. In order to make the cooperation between the two groups meaningful and guarantee the quality of service (QoS) requirements of both groups, the minimal required data rates of the two groups are considered as constraints for the optimal system design. As both problems are non-convex and have no known solutions, we solve it by using proper variable substitutions and the semi-definite relaxation (SDR). We theoretically prove that our proposed solution method can guarantee to find the global optimal solution. Thirdly, consider that the WPCN has promising application potentials in future energy-constrained net- works, e.g., wireless sensor network (WSN), wireless body area network (WBAN) and Internet of Things (IoT), where the power consumption is very critical. We investigate the minimal power consumption optimal design for the considered co- operation WPCN. For this, we formulate an optimization problem to minimize the total consumed power by jointly optimizing the time assignment, power allocation, and energy beamforming under required data rate constraints. As the problem is also non-convex and has no known solutions, we solve it by using some variable substitutions and the SDR method. We also theoretically prove that our proposed solution method for the minimal power consumption design guarantees the global optimal solution. Extensive experimental results are provided to discuss the system performance behaviors, which provide some useful insights for future WPCN design. It shows that the average power constrained system achieves higher weighted sum rate than the fixed power constrained system. Besides, it also shows that in such a WPCN, relay should be placed closer to the multi-antenna H-AP to achieve higher weighted sum rate and consume lower total power.