１ Ｂａｓｉｃ ｎｅｐｈｒｏｌｏｇｙ（生理；免疫・病理；分子生物学；検査・診断） ２ Ｃｌｉｎｉｃａｌ ｎｅｐｈｒｏｌｏｇｙ（糸球体障害；尿細管・間質障害；全身性疾患と腎障害；水電解質異常；腎不全）

Annual review 腎臓

In response to strong growth in air transportation CO2 emissions, governments and industry began to explore and implement mitigation measures and targets in the early 2000s. However, in the absence of rigorous analyses assessing the costs for mitigating CO2 emissions, these policies could be economically wasteful. Here we identify the cost-effectiveness of CO2 emission reductions from narrow-body aircraft, the workhorse of passenger air transportation. We find that in the US, a combination of fuel burn reduction strategies could reduce the 2012 level of life cycle CO2 emissions per passenger kilometre by around 2% per year to mid-century. These intensity reductions would occur at zero marginal costs for oil prices between US$50–100 per barrel. Even larger reductions are possible, but could impose extra costs and require the adoption of biomass-based synthetic fuels. The extent to which these intensity reductions will translate into absolute emissions reductions will depend on fleet growth. The US aviation sector is the world’s largest single air transportation system. Modelling shows that fuel burn strategies could reduce emissions from narrow-body passenger aircraft by 2% per kilometre travelled, at zero marginal cost.

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Costs of mitigating CO2 emissions from passenger aircraft

The ever-increasing demand for passenger air traffic results in larger airline fleets every year. The aircraft market forecast reveals an unprecedented growth for the coming decades, leading to serious environmental and economic concerns among airlines and regulatory bodies. Different approaches, for both airborne and ground operations, have been proposed to reduce and control emissions without compromising profit margin. For on-ground activities, the electric taxiing (ET) methodology is one of the suggested solutions for reducing the emissions and the acoustic noise in the airport, and for lowering the fuel consumption and operating costs. This article, thus, aims to review and collate the more important literature related to ET systems, in order to draw an inclusive picture regarding the current state-of-the-art of a moving and growing sector that just started its first steps toward an ambitious target. After introducing the general concept of ET, elaborations on the benefits and challenges of available technologies are done with a detailed comparison of the different systems. Finally, recommendations for future research and outlook on ET are presented.

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Review, Challenges, and Future Developments of Electric Taxiing Systems

Aviation is a mode with high fuel consumption per passenger mile and has significant environmental impacts. It is important to seek ways to reduce fuel consumption by the aviation sector, but it is difficult to improve fuel efficiency during the en-route cruise phase of flight because of technology barriers, safety requirements, and the mode of operations of air transportation. Recent efforts have emphasized the development of innovative Aircraft Ground Propulsion Systems (AGPS) for electrified aircraft taxi operations. These new technologies are expected to significantly reduce aircraft ground-movement-related fuel burn and emissions. This study compares various emerging AGPS systems and presents a comprehensive review on the merits and demerits of each system, followed with the local environmental impacts assessment of these systems. Using operational data for the 10 busiest U.S. airports, a comparison of environmental impacts is performed for four kinds of AGPS: conventional, single engine-on, external, and on-board systems. The results show that there are tradeoffs in fuel and emissions among these emerging technologies. On-board system shows the best performance in the emission reduction, while external system shows the least fuel burn. Compared to single-engine scenario, external AGPS shows the reduction of HC and CO emissions but the increase of NO x emission. When a general indicator is considered, on-board AGPS shows the best potential of reducing local environmental impacts. The benefit-cost analysis shows that both external and on-board systems are worth being implemented and the on-board system appeals to be more beneficial.

Comparison of emerging ground propulsion systems for electrified aircraft taxi operations

Airport ground operations have a great impact on the surrounding environment. Many have proposed or are studying innovative systems to perform taxi without use of the main engines. This would result in cleaner and quieter airport operations, as well as in improved fuel efficiency. In this paper, the possibilities and limitations of such systems are discussed considering real scenarios and constraints. The technical challenges that determine their viability and integrability into the aircraft or airport, as well as the expected benefits and issues are addressed. Finally, the most important current research and development projects are presented.

Viability and state of the art of environmentally friendly aircraft taxiing systems

In this study the potential for fuel savings through electric taxiing is investigated. Therefore simple models are used to investigate the difference of fuel consumption during the ground phase and the flight phase of a gate-to-gate mission. By using these models the fuel savings can be estimated, which are the sum of the fuel saved during ground operations and the additional fuel required during the flight phase due to an increased Operating Empty Weight. The models are applied to actual data of flights conducted by domestic carriers within the United States National Airspace System. Results show that electric taxiing offers the potential for fuel savings depending on the flight mission, i.e. the ratio of time an aircraft spends on ground and the flight distance. A parametric analysis is conducted to investigate the sensitivity of the results for different constraints. The study concludes with a comparison of the concept compared to other operational or technological measures aiming to reduce fuel consumption on ground.

Potential for Fuel Reduction through Electric Taxiing

The current push in automation, communication, and electrical energy storage technologies has the potential to lift urban mobility into the sky. As several urban air mobility (UAM) concepts are conceivable, all relevant physical effects as well as mutual interrelations of the UAM system have to be addressed and evaluated at a sufficient level of fidelity before implementation. Therefore, a collaborative system of systems modeling approach for UAM is presented. To quickly identify physical effects and cross-disciplinary influences of UAM, a pool of low-fidelity physical analysis components is developed and integrated into the Remote Component Environment (RCE) workflow engine. This includes, i. a., the disciplines of demand forecast, trajectory, vertiport, and cost modeling as well as air traffic flow and capacity management. The definition and clarification of technical interfaces require intensive cooperation between specialists with different areas of expertise. To reduce this communication effort, the Common Parametric Aircraft Configuration Schema (CPACS) is adapted and used as central data exchange format. The UAM system module is initially applied for a 24-hour simulation of three generic networks in Hamburg City. After understanding the basic system-level behavior, higher level analysis components and feedback loops must be integrated in the UAM system module for evaluation and optimization of explicit operating concepts.

A Collaborative Approach for an Integrated Modeling of Urban Air Transportation Systems

There is a considerable interest in air transportation resilience as a mechanism to cope with the consequences of disruptions to local authorities. Although the identification of metrics and baselines for measuring resilience are still regarded as challenges, we believe that the meaning of disruptions is no longer driven solely by safety threats but also by emergent performance issues. In this paper, resilience of the European Air Traffic Management Network (EATMN) is studied from a performance perspective. In fact, improved predictability and reliability of planning data across the EATMN, allow reduction of reserved Air Traffic Management (ATM) capacity. Consequently, the management of emergent demand-capacity imbalances, regarded as disruptions, is added to tactical phase of Air Fraffic Flow and Capacity Management (ATFCM). In this phase of operations (i.e. day-of-operations) a limited number of variables are available to form aggregated indicators for network resilience. We consider that available ATFCM regulations data reveal restorative mechanisms for tactical Demand-Capacity Balancing (DCB). Aggregated indicators are regarded as enablers to monitor the resilient management of Area Control Centers and to observe spatial distribution of network resiliency. This paper presents an exploratory effort of the needed situational awareness by exploring supervised learning techniques in the context of ATFCM regulations to predict Air Traffic Flow Management (ATFM) delay. In particular, it focuses on the application of machine learning algorithms and comparison of different architecture variants to a regression study on tactical DCB disruptions.

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Machine Learning Application in Network Resiliency based on Capacity Regulations

The purpose of this paper is to evaluate a slot 
allocation heuristic algorithm close to Eurocontrol‘
s Computer-Aided-Slot-Allocation. The
heuristic algorithm represents a First-Planned-
First-Serve approach for tactical Air Traffic Flow
Management slot allocation in order to balance
air traffic demand with network capacities. It is
part of DLR‘s Network Flow Environment (NFE)
introduced in this paper, which allocates tactical
Air Traffic Flow Management slots throughout
the whole European Air Traffic Management
Network by satisfying the objective of optimal
network delay minimization. In order to quantify
delay cost reduction applying a binary integer
programming approach, the First-Planned-
First-Serve heuristic serves as delay allocation
reference for individual adverse impact scenarios.
Short-term convective forecasts (nowcasts)
serve as use-case to generate demand-capacityimbalances.
It shows, that the First-Planned-
First-Serve heuristic is capable to generate representative
slot allocation data for operational scenario
setups. In terms of delay performance, results
can be improved by optimization for largescale
Air Traffic Flow Management problems.

The Network Flow Environment: Slot Allocation Model Evaluation With Convective Nowcasting

To guarantee a safe journey for each aircraft, air traffic controllers make sure that separation minima are maintained. To prevent controller overburdening, each controller team is responsible for one confined sector. Furthermore, sectors limit the number of flights entering each hour. Compliance to all sector and airport capacity constraints in daily business is ensured by EUROCONTROL’s Network Management. This function balances the flights’ demand of airspace with available capacity by re-allocating departure timeslots. However, when minimum separation between two aircraft may become compromised, a conflict occurs. Conflicts are solved by controllers who provide pilots with instructions to maintain separation. Hence, conflicts increase controller workload and thus tighten sector capacity. The aim of this work is a prevention of actual conflicts by strategic deconfliction. Strategic conflicts refer to planned trajectories which violate separation minima in any future point in space and time. Mimicking a future Network Management, departure times are re-allocated to reduce the number of strategic conflicts while satisfying both sector and airport capacity constraints. As a basis for the deconfliction, actual datasets of planned trajectories, sector bounds and airport features are aggregated to model the European Air Traffic Flow Management. The allocation problem of departure timeslots is formulated as a Quadratic Binary Problem with linear delay costs, quadratic conflict costs and linear constraints. In an optimal solution, all strategic conflicts are solved. Finally, a trade-off between conflict reduction and delay is performed.

Alexander Lau

Papers

Potential for Fuel Reduction through Electric Taxiing

A Collaborative Approach for an Integrated Modeling of Urban Air Transportation Systems

Machine Learning Application in Network Resiliency based on Capacity Regulations

The Network Flow Environment: Slot Allocation Model Evaluation With Convective Nowcasting

European Air Traffic Flow Management with Strategic Deconfliction