Baseline measurements of ethene in 2002: Implications for increased ethanol use and biomass burning on air quality and ecosystems

While it is well known that combustion of ethanol as a biofuel will lead to enhanced emissions of methane, ethene (ethylene), acetaldehyde, formaldehyde, and oxides of nitrogen (primarily NO) when compared to gasoline alone, especially during cold starts or if catalytic converters are not operating properly, the impacts of increases in atmospheric ethene levels from combustion of fuels with higher ethanol content has not received much attention. Ethene is a well known and potent plant growth hormone and exposure to agricultural crops and natural vegetation results in yield reductions especially when combined with higher levels of PAN and ozone also expected from the increased use of ethanol/gasoline blends. We report here some baseline measurements of ethene obtained in 2002 in the southwestern and south central United States. These data indicate that current ethene background levels are less than 1 ppb. Anticipated increases in fuel ethanol content of E30 or greater is expected to lead to higher atmospheric levels of ethene on regional scales due to its atmospheric lifetime of 1.5-3 days. These background measurements are discussed in light of the potential enhancement of ethene levels expected from the anticipated increases in ethanol use as a renewable biofuel. © 2012 Elsevier Ltd

Constraints on Asian and European sources of methane from Ch 4-C2H6-CO correlations in Asian outflow

Aircraft observations of Asian outflow from the Transport and Chemical Evolution Over the Pacific (TRACE-P) aircraft mission over the NW Pacific (March and April 2001) show large CH4 enhancements relative to background, as well as strong CH4-C2H 6-CO correlations that provide signatures of regional sources. We apply a global chemical transport model simulation of the CH4-C2H6-CO system for the TRACE-P period to interpret these observations in terms of CH4 sources and to explore in particular the unique constraints from the CH 4-C2H6-CO correlations. We use as a priori a global CH4 source inventory constrained with National Oceanic and Atmospheric Administration (NOAA) Climate Monitoring and Diagnostics Laboratory (CMDL) surface observations [Wang et al., 2004]. We find that the observed CH4 concentration enhancements and CH4-C2H6-CO correlations in Asian outflow in TRACE-P are deterinined mainly by anthropogenic emissions from China and Eurasia (defined here as Europe and eastern Russia), with only little contribution from tropical sources (wetlands and biomass burning). The a priori inventory overestimates the observed CH4 enhancements and shows regionally variable biases for the CH4/C2H6 slope. The CH 4/CO slopes are simulated without significant bias. Matching both the observed CH4 enhancements and the CH 4-C2H6-CO slopes in Asian outflow requires increasing the east Asian anthropogenic source of CH 4, and decreasing the Eurasian anthropogenic source, by at least 30% for both. The need to increase the east Asian source is driven by the underestimate of the CH4/C2H 6 slope in boundary layer Chinese outflow. The Streets et al. [2003] anthropogenic emission inventory for east Asia fits this constraint by increasing CH4 emissions from that region by 40% relative to the a priori, largely because of higher livestock and landfill source estimates. Eurasian sources (mostly European) then need to be reduced by 30-50% from the a priori value of 68 Tg yr -1. The decrease of European sources could result in part from recent mitigation of emissions from coal mining and landfills. Copyright 2004 by the American Geophysical Union

The Pandora multi-algorithm approach to automated pattern recognition in LAr TPC detectors

The development and operation of Liquid Argon Time Projection Chambers (LAr TPCs) for neutrino physics has created a need for new approaches to pattern recognition, in order to fully exploit the superb imaging capabilities offered by this technology. The Pandora Software Development Kit provides functionality to aid the process of designing, implementing and running pattern recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition: individual algorithms each address a specific task in a particular topology; a series of many tens of algorithms then carefully builds-up a picture of the event. The input to the Pandora pattern recognition is a list of 2D Hits. The output from the chain of over 70 algorithms is a hierarchy of reconstructed 3D Particles, each with an identified particle type, vertex and direction

Ozone and alkyl nitrate formation from the Deepwater Horizon oil spill atmospheric emissions

Ozone (O3), alkyl nitrates (RONO2), and other photochemical products were formed in the atmosphere downwind from the Deepwater Horizon (DWH) oil spill by photochemical reactions of evaporating hydrocarbons with NOx (=NO+NO2) emissions from spill response activities. Reactive nitrogen species and volatile organic compounds (VOCs) were measured from an instrumented aircraft during daytime flights in the marine boundary layer downwind from the area of surfacing oil. A unique VOC mixture, where alkanes dominated the hydroxyl radical (OH) loss rate, was emitted into a clean marine environment, enabling a focused examination of O3 and RONO 2 formation processes. In the atmospheric plume from DWH, the OH loss rate, an indicator of potential O3 formation, was large and dominated by alkanes with between 5 and 10 carbons per molecule (C 5-C10). Observations showed that NOx was oxidized very rapidly with a 0.8h lifetime, producing primarily C6-C10 RONO2 that accounted for 78% of the reactive nitrogen enhancements in the atmospheric plume 2.5h downwind from DWH. Both observations and calculations of RONO2 and O3 production rates show that alkane oxidation dominated O3 formation chemistry in the plume. Rapid and nearly complete oxidation of NOx to RONO2 effectively terminated O3 production, with O3 formation yields of 6.0±0.5 ppbv O3 per ppbv of NOx oxidized. VOC mixing ratios were in large excess of NOx, and additional NOx would have formed additional O3 in this plume. Analysis of measurements of VOCs, O3, and reactive nitrogen species and calculations of O3 and RONO2 production rates demonstrate that NOx-VOC chemistry in the DWH plume is explained by known mechanisms. Copyright 2012 by the American Geophysical Union

Emission estimates of HCFCs and HFCs in California from the 2010 CalNex study

The CalNex 2010 (California Research at the Nexus of Air Quality and Climate Change) study was designed to evaluate the chemical composition of air masses over key source regions in California. During May to June 2010, air samples were collected on board a National Oceanic and Atmospheric Administration (NOAA) WP-3D aircraft over the South Coast Air Basin of California (SoCAB) and the Central Valley (CV). This paper analyzes six effective greenhouse gases - chlorodifluoromethane (HCFC-22), 1,1-dichloro-1-fluoroethane (HCFC-141b), 1-chloro-1,1-difluoroethane (HCFC-142b), 2-chloro-1,1,1,2-tetrafluoroethane (HCFC-124), 1,1,1,2- tetrafluoroethane (HFC-134a), and 1,1-difluoroethane (HFC-152a) - providing the most comprehensive characterization of chlorofluorocarbon (CFC) replacement compound emissions in California. Concentrations of measured HCFCs and HFCs are enhanced greatly throughout the SoCAB and CV, with highest levels observed in the SoCAB: 310 ± 92 pptv for HCFC-22, 30.7 ± 18.6 pptv for HCFC-141b, 22.9 ± 2.0 pptv for HCFC-142b, 4.86 ± 2.56 pptv for HCFC-124, 109 ± 46.4 pptv for HFC-134a, and 91.2 ± 63.9 pptv for HFC-152a. Annual emission rates are estimated for all six compounds in the SoCAB using the measured halocarbon to carbon monoxide (CO) mixing ratios and CO emissions inventories. Emission rates of 3.05 ± 0.70 Gg for HCFC-22, 0.27 ± 0.07 Gg for HCFC-141b, 0.06 ± 0.01 Gg for HCFC-142b, 0.11 ± 0.03 Gg for HCFC-124, 1.89 ± 0.43 Gg for HFC-134a, and 1.94 ± 0.45 Gg for HFC-152b for the year 2010 are calculated for the SoCAB. These emissions are extrapolated from the SoCAB region to the state of California using population data. Results from this study provide a baseline emission rate that will help future studies determine if HCFC and HFC mitigation strategies are successful. Key PointsHCFC and HFC emissions are calculated for the year 2010 for the SoCABEmissions are extrapolated to the state of CaliforniaEmissions are calculated using CalNex field measurements © 2013. American Geophysical Union. All Rights Reserved

Determination of urban volatile organic compound emission ratios and comparison with an emissions database

During the NEAQS-ITCT2k4 campaign in New England, anthropogenic VOCs and CO were measured downwind from New York City and Boston. The emission ratios of VOCs relative to CO and acetylene were calculated using a method in which the ratio of a VOC with acetylene is plotted versus the photochemical age. The intercept at the photochemical age of zero gives the emission ratio. The so determined emission ratios were compared to other measurement sets, including data from the same location in 2002, canister samples collected inside New York City and Boston, aircraft measurements from Los Angeles in 2002, and the average urban composition of 39 U.S. cities. All the measurements generally agree within a factor of two. The measured emission ratios also agree for most compounds within a factor of two with vehicle exhaust data indicating that a major source of VOCs in urban areas is automobiles. A comparison with an anthropogenic emission database shows less agreement. Especially large discrepancies were found for the C2-C4 alkanes and most oxygenated species. As an example, the database overestimated toluene by almost a factor of three, which caused an air quality forecast model (WRF-CHEM) using this database to overpredict the toluene mixing ratio by a factor of 2.5 as well. On the other hand, the overall reactivity of the measured species and the reactivity of the same compounds in the emission database were found to agree within 30%. Copyright 2007 by the American Geophysical Union

Sensitivity of an Ultrasonic Technique for Axial Stress Determination

In machine assembly it is often required that bolts used to fasten machine parts be installed with specific design preloads. Because it is inconvenient to measure preload directly, preload specifications are usually based on some more easily measured quantity with which the level of preload may be correlated. Most often this quantity is the torque to be applied to the bolt at installation. Studies by Blake and Kurtz [1] and Heyman [2] have shown that when bolts are torqued into place, the fraction of applied torque which translates into useful preload is small and widely variable. This is so because the large majority of applied torque is absorbed in overcoming friction in the bolt’s threads and at the underside of the bolt’s head. Consequently, even though the torque to install different bolts may be identical, small variations in frictional conditions from one installation to the next can result in large variations in preload. The unreliability of torque as an indicator of preload has been the motivating factor behind the development of a number of alternate methods of measurement [2–5]

Airborne observations of methane emissions from rice cultivation in the Sacramento Valley of California

Airborne measurements of methane (CH4) and carbon dioxide (CO2) were taken over the rice growing region of California's Sacramento Valley in the late spring of 2010 and 2011. From these and ancillary measurements, we show that CH4 mixing ratios were higher in the planetary boundary layer above the Sacramento Valley during the rice growing season than they were before it, which we attribute to emissions from rice paddies. We derive daytime emission fluxes of CH4 between 0.6 and 2.0% of the CO2 taken up by photosynthesis on a per carbon, or mole to mole, basis. We also use a mixing model to determine an average CH 4/CO2 flux ratio of -0.6% for one day early in the growing season of 2010. We conclude the CH4/CO2 flux ratio estimates from a single rice field in a previous study are representative of rice fields in the Sacramento Valley. If generally true, the California Air Resources Board (CARB) greenhouse gas inventory emission rate of 2.7×1010g CH4/yr is approximately three times lower than the range of probable CH4 emissions (7.8-9.3×10 10g CH4/yr) from rice cultivation derived in this study. We attribute this difference to decreased burning of the residual rice crop since 1991, which leads to an increase in CH4 emissions from rice paddies in succeeding years, but which is not accounted for in the CARB inventory. © 2012. American Geophysical Union. All Rights Reserved

An Overview of the Use of Neural Networks for Data Mining Tasks

In the recent years the area of data mining has experienced a considerable demand for technologies that extract knowledge from large and complex data sources. There is a substantial commercial interest as well as research investigations in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from datasets. Artificial Neural Networks (NN) are popular biologically inspired intelligent methodologies, whose classification, prediction and pattern recognition capabilities have been utilised successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks