Airlines and Air Navigation Service Providers are united in their goal to reduce fuel consumption. While changes to flight operations and technology investments are the focus of a number of studies, our study is among the first to investigate an untapped source of aviation fuel consumption: excess contingency fuel loading. Given the downside risk of fuel exhaustion of diverting to an alternate airport, airline dispatchers may load excess fuel onto an aircraft. Such conservatism comes at a cost of consuming excess fuel, as fuel consumed is a function of, among other factors, aircraft weight. The aim of this paper is to quantify, on a per-flight basis, the fuel burned due to carrying fuel beyond what is needed for foreseeable contingencies, and thereby motivate research, federal guidance, and investments that allow airline dispatchers to reduce fuel uplift while maintaining near zero risks of fuel exhaustion. We merge large publicly available aviation and weather databases with a detailed dataset from a major US airline. Upon estimating factors that capture the quantity fuel consumed due to carrying a pound of weight for a range of aircraft types, we calculate the cost and greenhouse gas emissions from carrying unused fuel on arrival and additional contingency fuel above a conservative buffer for foreseeable contingencies. We establish that the major US carrier does indeed load fuel conservatively. We find that 4.48% of the fuel consumed by an average flight is due to carrying unused fuel and 1.04% of the fuel consumed by an average flight is due to carrying additional contingency fuel above a reasonable buffer. We find that simple changes in flight dispatching that maintain a statistically minimal risk of fuel exhaustion could result in yearly savings of 338 million lbs of CO 2 , the equivalent to the fuel consumed from 4760 flights on midsized commercial aircraft. Moreover, policy changes regarding maximum fuel loads or investments that reduce uncertainty or increase the ability to plan flights under uncertainty could yield far greater benefits.
More and more attention has been paid to the development of renewable energy in the world. Microgrids with flexible regulation abilities provide an effective way to solve the problem of renewable energy connected to power grids. In this article, an optimization strategy of a microgrid participating in day-ahead market operations considering demand responses is proposed, where the uncertainties of distributed renewable energy generation, electrical load, and day-ahead market prices are taken into account. The results show that, when the microgrid implements the demand response, the operation cost of the microgrid decreases by 4.17%. Meanwhile, the demand response program can transfer the peak load of the high-price period to the low-price period, which reduces the peak valley difference of the load and stabilizes the load curve. Finally, a sensitivity analysis of three factors is carried out, finding that, with the increase of the demand response adjustable ratio or the maximum capacity of the electrical storage devices, the operation cost of the microgrid decreases, while, with the increase of the demand response cost, the operation cost of the microgrid increases and, finally, tends to the cost without the demand response. The sensitivity analysis reveals that the demand response cost has a reasonable pricing range to maximize the value of the demand response.
This paper empirically investigates the interactions among CO 2 emissions, economic growth, and three selected types of fossil energy consumption (coal, gas, and oil) using time series data from China over the period 1965-2015. Classic econometric analysis technologies including the Johansen cointegration test, the vector error correction model (VECM), and the Granger causality test based on VECM are employed to meet our objectives, and the presence of breaks in the data is also considered. Cointegration test result supports the existence of a long-run equilibrium relationship among the five variables, and the error correction mechanisms of the system involving the five variables are proven to be effective by VECM. Additionally, the Granger causality test based on VECM reveals that the bidirectional causalities between GDP and coal consumption, between GDP and gas consumption, and between coal consumption and CO 2 emissions and unidirectional causalities running from GDP and oil consumption to CO 2 emissions, from GDP to oil consumption, and from coal consumption to oil and gas consumption are found. Furthermore, several policy implications are proposed in the final section of this paper based on the empirical results.
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