Corrosion of aluminum alloy 2024 by microorganisms isolated from aircraft fuel tanks

Abstract

Microorganisms frequently contaminate jet fuel and cause corrosion of fuel tank metals. In the past, jet fuel contaminants included a diverse group of bacteria and fungi. The most common contaminant was the fungus Hormoconis resinae. However, the jet fuel community has been altered by changes in the composition of the fuel and is now dominated by bacterial contaminants. The purpose of this research was to determine the composition of the microbial community found in fuel tanks containing jet propellant-8 (JP-8) and to determine the potential of this community to cause corrosion of aluminum alloy 2024 (AA2024). Isolates cultured from fuel tanks containing JP-8 were closely related to the genus Bacillus and the fungi Aureobasidium and Penicillium. Biocidal activity of the fuel system icing inhibitor diethylene glycol monomethyl ether is the most likely cause of the prevalence of endospore forming bacteria. Electrochemical impedance spectroscopy and metallographic analysis of AA2024 exposed to the fuel tank environment indicated that the isolates caused corrosion of AA2024. Despite the limited taxonomic diversity of microorganisms recovered from jet fuel, the community has the potential to corrode fuel tanks.     

Aerial Surveys for Estimating Wild Turkey Abundance in the Texas Rolling Plains

Abstract: Aerial surveys have been used to estimate abundance of several wild bird species including wild turkeys (Meleagris gallopavo). We used inflatable turkey decoys at 3 study sites in the Texas Rolling Plains to simulate Rio Grande wild turkey (M. g. intermedia) flocks. We evaluated detectability of flocks and errors in counting flock size during fixed-wing (Cessna 172) aerial surveys using logistic and linear regression models. Flock detectability was primarily influenced by flock size and vegetative cover, and errors in counting flock size were primarily influenced by size of flocks. We conducted computer simulations to evaluate the accuracy and precision of fixed-wing aerial surveys and examined power to detect trends in population change. Our simulations suggested abundance estimates from fixed-wing aerial surveys may be underestimated by 10-15% (2.0-4.8% CV). Power analyses suggested that fixed-wing aerial surveys can provide sufficient power (>0.80) to detect a population change of 10-25% over a 4-5-year period. We concluded fixed-wing aerial surveys are feasible on ecoregion scales.     

Net regional ecosystem CO2 exchange from airborne and ground-based eddy covariance, land-use maps and weather observations

Measurements of regional net ecosystem exchange (NEE) were made over a period of 21 days in summer 2002 in the South‐Central part of the Netherlands and extrapolated to an area of 13 000 km² using a combination of flux measurements made by a Sky Arrow ERA research aircraft, half‐hourly eddy covariance data from four towers, half‐hourly weather data recorded by three weather stations and detailed information on regional land use. The combination of this type of information allowed to estimate the net contribution of the terrestrial ecosystems to the overall regional carbon flux and to map dynamically the temporal and spatial variability of the fluxes. A regional carbon budget was calculated for the study period and the contributions of the different land uses to the overall regional flux, were assessed. Ecosystems were, overall, a small source of carbon to the atmosphere equivalent to to 0.23±0.025 g C m⁻² day⁻¹. When considered separately, arable and grasslands were a source of, respectively, 0.68±0.022 and 1.28±0.026 g C m⁻² day⁻¹. Evergreen and deciduous forests were instead a sink of −1.42±0.015 g C m⁻² day⁻¹. During the study period, forests offset approximately 3.5% of anthropogenic carbon emission estimates obtained from inventory data. Lacking of a robust validation, NEE values obtained with this method were compared with independent state of art estimates of the regional carbon balance that were obtained by applying a semi‐empirical model of NEE driven by MODIS satellite fAPAR data. The comparison showed an acceptable matching for the carbon balance of forest that was a sink in both cases, while a much larger difference for arable and grassland was found. Those ecosystems were a sink for satellite‐based estimates while they were a source for the combined aircraft and tower estimates. Possible causes of such differences are discussed and partly addressed. The importance of new methods for determining carbon balance at the regional scale, is outlined.     

A large impact of tropical biomass burning on CO and CO2 in the upper troposphere

A large interannual variation of biomass burning emissions from Southeast Asia is asso-ciated with the ENSO events. During 1997/98 and 1994 El Nino years, uncontrolled wildfires of tropical rainforests and peat lands in Indonesia were enlarged due to a long drought. EnhancedCO injection into the upper troposphere from the intense Indonesian fires was clearly observed in the 8-year measurements from a regular flask sampling over the western Pacific using a JAL air-liner between Australia and Japan. This airliner observation also revealed that upper tropospheric CO_2 cycle largely changed during the 1997 El Nino year due partly to the biomass burning emis-sions. Widespread pollution from the biomass burnings in Southeast Asia was simulated using aCO tracer driven by a 3D global chemical transport model. This simulation indicates that tropical deep convections connected to rapid advection by the subtropical jet play a significant role in dis-persing biomass-burning emissions from Southeast Asia on a global scale.     

Candida keroseneae sp. nov., a novel contaminant of aviation kerosene

Aims: To characterize and identify a novel contaminant of aviation fuel. Methods and Results: Micro‐organisms (yeasts and bacteria) were isolated from samples of aviation fuel. A yeast that proved to have been unrecorded previously was isolated from more than one fuel sample. This novel yeast proved to be a new species of Candida and is described here. Ribosomal RNA gene sequence analyses of internal transcribed spacer (ITS) regions (including 5·8S subunit) plus the 26S D1/D2 domains showed the strains to cluster within the Candida membranifaciens clade nearest to, but distinct from, Candida tumulicola. Phenotypic tests were identical for both isolates. Physiological and biochemical tests supported their position as a separate taxon. The yeast was assessed for its effect on the main constituent hydrocarbons of aviation fuel. Conclusions: Two strains (IMI 395605^T and IMI 395606) belonging to the novel yeast species, Candida keroseneae, were isolated from samples of aircraft fuel (kerosene), characterized and described herein with reference to their potential as contaminants of aviation fuel. Significance and Impact of the Study: As a result of isolating a novel yeast from aviation fuel, the implications for microbial contamination of such fuel should be considered more widely than previously thought.     

Detection of respiratory viruses on air filters from aircraft

Aims: To evaluate the feasibility of identifying viruses from aircraft cabin air, we evaluated whether respiratory viruses trapped by commercial aircraft air filters can be extracted and detected using a multiplex PCR, bead‐based assay. Methods and Results: The ResPlex II assay was first tested for its ability to detect inactivated viruses applied to new filter material; all 18 applications of virus at a high concentration were detected. The ResPlex II assay was then used to test for 18 respiratory viruses on 48 used air filter samples from commercial aircraft. Three samples tested positive for viruses, and three viruses were detected: rhinovirus, influenza A and influenza B. For 33 of 48 samples, internal PCR controls performed suboptimally, suggesting sample matrix effect. Conclusion: In some cases, influenza and rhinovirus RNA can be detected on aircraft air filters, even more than 10 days after the filters were removed from aircraft. Significance and Impact of the Study: With protocol modifications to overcome PCR inhibition, air filter sampling and the ResPlex II assay could be used to characterize viruses in aircraft cabin air. Information about viruses in aircraft could support public health measures to reduce disease transmission within aircraft and between cities.     

Vulture flight behavior and implications for aircraft safety

Growing vulture populations represent increasing hazards to civil and military aircraft. To assess vulture flight behavior and activity patterns at the Marine Corps Air Station in Beaufort, South Carolina, we equipped 11 black vultures (Coragyps atratus) and 11 turkey vultures (Cathartes aura) with solar-powered Global Positioning System (GPS) satellite transmitters during a 2-year study (1 Oct 2006–30 Sep 2008). Turkey vultures had larger seasonal home ranges than did black vultures, and 2 turkey vultures made round-trips to Florida. Black vultures consistently spent less time in flight (8.4%) than did turkey vultures (18.9%), and black vultures flew at higher altitudes than did turkey vultures in all seasons except summer when altitudinal distributions (above ground level) did not differ. Although we recorded maximum altitudes of 1,578 m for black vultures and 1,378 for turkey vultures, most flights were low altitude. A matrix of vulture flight altitude versus time of day revealed that >60% of vulture flight activity occurred from 4 hr to 9 hr after sunrise at altitudes below 200 m. Continuation of aggressive harassment coupled with flexible training schedules to avoid times and altitudes of high vulture activity will decrease hazards to aircraft posed by these birds. © 2011 The Wildlife Society.     

基于无人机和决策树算法的榆树疏林草原植被类型划分和覆盖度生长季动态估计

植被覆盖度是评估生态环境质量与植被生长的重要指标,也是全球众多陆面过程模型和生态系统模型中表达植被动态的重要参数。卫星遥感和地面测量是估算植被覆盖度的常见方法。然而,如何精确估计榆树疏林草原上木本、草本不同类型植被的覆盖度仍然具有挑战性。无人机飞行系统有效的补充了区域尺度低空间分辨率的卫星遥感影像与样地尺度实地调查之间的缺口,为精确的监测、评估疏林草原的植被动态提供了新途径。利用无人机监测平台和决策树算法构建了一套快速、准确、自动获取景观尺度植被类型和估算植被覆盖度的自动化工具,以浑善达克沙地榆树疏林草原为对象,应用无人机监测平台对榆树疏林草原长期定位监测大样地2017年生长季植被状况进行7次监测。结果表明:1)无人机植被监测平台数据飞行高度100 m,获取的样地数字正射影像空间分辨率为2.67 cm/像元,远高于高分卫星影像,利用决策树算法基于数字正射影像可以实现自动划分榆树疏林草原木本和草本植被类型和估算植被覆盖度; 2)生长季内榆树疏林草原木本植被覆盖度为(19±2)%,草本植被覆盖度为(50±8)%,植被总覆盖度为(69±9)%,相对于木本植被,草本植被生长季内盖度变幅较大; 3)在整个生长季中,木本植被和草本植被对植被总覆盖度的平均贡献率分别为27%和73%,草本植被对植被总盖度的贡献远大于木本植被,榆树疏林草原植被的盖度主要受草本植被的影响。本研究证明无人机监测平台是一种高效、准确的植被监测工具,结合机器学习算法,实现了景观尺度植被类型的自动划分和不同类型植被覆盖度快速获取;在浑善达克沙地榆树疏林草原地区首次获取了木本植被和草本植被覆盖度的生长季动态。该平台未来可应用于各种类型生态系统植被类型划分、监测和评估。