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Greenhouse gas emissions mitigation requires understanding the dominant processes controlling fluxes of these trace gases at increasingly finer spatial and temporal scales. Trace gas fluxes can be estimated using a variety of approaches that translate observed atmospheric species mole fractions into fluxes or emission rates, often identifying the spatial and temporal characteristics of the emission sources as well. Meteorological models are commonly combined with tracer dispersion models to estimate fluxes using an inverse approach that optimizes emissions to best fit the trace gas mole fraction observations. One way to evaluate the accuracy of atmospheric flux estimation methods is to compare results from independent methods, including approaches in which different meteorological and tracer dispersion models are used. In this work, we use a rich data set of atmospheric methane observations collected during an intensive airborne campaign to compare different methane emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We estimate emissions based on a variety of different meteorological and dispersion models. Previous estimates of methane emissions from this region relied on a simple model (a mass balance analysis) as well as on ground-based measurements and statistical data analysis (an inventory). We find that in addition to meteorological model choice, the choice of tracer dispersion model also has a significant impact on the predicted downwind methane concentrations given the same emissions field. The dispersion models tested often underpredicted the observed methane enhancements with significant variability (up to a factor of 3) between different models and between different days. We examine possible causes for this result and find that the models differ in their simulation of vertical dispersion, indicating that additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models commonly used in regional trace gas flux inversions.

Urban areas contribute approximately three-quarters of fossil fuel derived CO2 emissions, and many cities have enacted emissions mitigation plans. Evaluation of the effectiveness of mitigation efforts will require measurement of both the emission rate and its change over space and time. The relative performance of different emission estimation methods is a critical requirement to support mitigation efforts. Here we compare results of CO2 emissions estimation methods including an inventory-based method and two different top-down atmospheric measurement approaches implemented for the Indianapolis, Indiana, U.S.A. urban area in winter. By accounting for differences in spatial and temporal coverage, as well as trace gas species measured, we find agreement among the wintertime whole-city fossil fuel CO2 emission rate estimates to within 7%. This finding represents a major improvement over previous comparisons of urban-scale emissions, making urban CO2 flux estimates from this study consistent with local and global emission mitigation strategy needs. The complementary application of multiple scientifically driven emissions quantification methods enables and establishes this high level of confidence and demonstrates the strength of the joint implementation of rigorous inventory and atmospheric emissions monitoring approaches.

A credible assessment of a city’s greenhouse gas (GHG) mitigation policies requires a valid account of a city’s emissions. However, questions persist as to whether cities’ ‘self-reported inventories’ (SRIs) are accurate, precise, and consistent enough to track progress toward city mitigation goals. Although useful for broad policy initiatives, city SRIs provide annual snapshots that may have limited use to city managers looking to develop targeted mitigation policies that overlap with other issues like equity, air quality, and human health. An emerging approach from the research community that integrates ‘bottom-up’ hourly, street-level emission data products with ‘top-down’ GHG atmospheric observations have begun to yield production-based (scope 1) GHG estimates that can track changes in emissions at annual and sub-annual timeframes. The use of this integrated approach offers a much-needed assessment of SRIs: the atmospheric observations are tied to international standards and the bottom-up information incorporates multiple overlapping socio-economic data. The emissions are mapped at fine scales which helps link them to attribute information (e.g. fuel types) that can further facilitate mitigation actions. Here, we describe this approach and compare results to the SRI from the City of Indianapolis which shows a yearly difference of 35% in scope 1 emissions. In the City of Baltimore, we show that granular emission information can help address multiple issues, e.g. GHG emissions, air pollution, and inequity, at the sub-zip code scale where many roots and causes for each issue exist. Finally, we show that the incorporation of atmospheric concentrations within an integrated system provides rapid, near-real-time feedback on CO2 emissions anomalies that can uncover important behavioral and economic relationships. An integrated approach to GHG monitoring, reporting and verification can ensure uniformity, and provide accuracy to city-scale GHG emissions, scalable to states and the nation—ultimately helping cities meet stated ambitions.

Advances in natural gas extraction technology have led to increased activity in the production and transport sectors in the United States and, as a consequence, an increased need for reliable monitoring of methane leaks to the atmosphere. We present a statistical methodology in combination with an observing system for the detection and attribution of fugitive emissions of methane from distributed potential source location landscapes such as natural gas production sites. We measure long (> 500 m), integrated open-path concentrations of atmospheric methane using a dual frequency comb spectrometer and combine measurements with an atmospheric transport model to infer leak locations and strengths using a novel statistical method, the non-zero minimum bootstrap (NZMB). The new statistical method allows us to determine whether the empirical distribution of possible source strengths for a given location excludes zero. Using this information, we identify leaking source locations (i.e., natural gas wells) through rejection of the null hypothesis that the source is not leaking. The method is tested with a series of synthetic data inversions with varying measurement density and varying levels of model–data mismatch. It is also tested with field observations of (1) a non-leaking source location and (2) a source location where a controlled emission of 3.1 × 10−5 kg s−1 of methane gas is released over a period of several hours. This series of synthetic data tests and outdoor field observations using a controlled methane release demonstrates the viability of the approach for the detection and sizing of very small leaks of methane across large distances (4+ km2 in synthetic tests). The field tests demonstrate the ability to attribute small atmospheric enhancements of 17 ppb to the emitting source location against a background of combined atmospheric (e.g., background methane variability) and measurement uncertainty of 5 ppb (1σ), when measurements are averaged over 2 min. The results of the synthetic and field data testing show that the new observing system and statistical approach greatly decreases the incidence of false alarms (that is, wrongly identifying a well site to be leaking) compared with the same tests that do not use the NZMB approach and therefore offers increased leak detection and sizing capabilities.

Natural gas infrastructure releases methane (CH4), a potent greenhouse gas, into the atmosphere. The estimated emission rate associated with the production and transportation of natural gas is uncertain, hindering our understanding of its greenhouse footprint. This study presents a new application of inverse methodology for estimating regional emission rates from natural gas production and gathering facilities in north-eastern Pennsylvania. An inventory of CH4 emissions was compiled for major sources in Pennsylvania. This inventory served as input emission data for the Weather Research and Forecasting model with chemistry enabled (WRF-Chem), and atmospheric CH4 mole fraction fields were generated at 3 km resolution. Simulated atmospheric CH4 enhancements from WRF-Chem were compared to observations obtained from a 3-week flight campaign in May 2015. Modelled enhancements from sources not associated with upstream natural gas processes were assumed constant and known and therefore removed from the optimization procedure, creating a set of observed enhancements from natural gas only. Simulated emission rates from unconventional production were then adjusted to minimize the mismatch between aircraft observations and model-simulated mole fractions for 10 flights. To evaluate the method, an aircraft mass balance calculation was performed for four flights where conditions permitted its use. Using the model optimization approach, the weighted mean emission rate from unconventional natural gas production and gathering facilities in north-eastern Pennsylvania approach is found to be 0.36 % of total gas production, with a 2σ confidence interval between 0.27 and 0.45 % of production. Similarly, the mean emission estimates using the aircraft mass balance approach are calculated to be 0.40 % of regional natural gas production, with a 2σ confidence interval between 0.08 and 0.72 % of production. These emission rates as a percent of production are lower than rates found in any other basin using a top-down methodology, and may be indicative of some characteristics of the basin that make sources from the north-eastern Marcellus region unique.

Urban areas are increasingly recognized as an important source of methane (CH4), but we have limited seasonally resolved observations of these regions. In this study, we quantify seasonal and annual urban CH4 emissions over the Baltimore, Maryland, and Washington, DC metropolitan regions. We use CH4 atmospheric observations from four tall tower stations and a Lagrangian particle dispersion model to simulate CH4 concentrations at these stations. We directly compare these simulations with observations and use a geostatistical inversion method to determine optimal emissions to match our observations. We use observations spanning four seasons and employ an ensemble approach considering multiple meteorological representations, emission inventories, and upwind CH4 values. Forward simulations in winter, spring, and fall underestimate observed atmospheric CH4 while in summer, simulations overestimate observations because of excess modeled wetland emissions. With ensemble geostatistical inversions, the optimized annual emissions in DC/Baltimore are 39 ± 9 Gg/month (1 δ), 2.0 ± 0.4 times higher than the ensemble mean of bottom-up emission inventories. We find a modest seasonal variability of urban CH4 emissions not captured in current inventories, with optimized summer emissions ∼41% lower than winter, broadly consistent with expectations if emissions are dominated by fugitive natural gas sources that correlate with natural gas usage.

We present in situ airborne measurements of methane (CH4) and ethane (C2H6) taken aboard a NOAA DHC-6 Twin Otter research aircraft in May 2014 over the Williston Basin in northwestern North Dakota, a region of rapidly growing oil and natural gas production. The Williston Basin is best known for the Bakken shale formation, from which a significant increase in oil and gas extraction has occurred since 2009. We derive a CH4 emission rate from this region using airborne data by calculating the CH4 enhancement flux through the planetary boundary layer downwind of the region. We calculate CH4 emissions of (36 ± 13), (27 ± 13), (27 ± 12), (27 ± 12), and (25 ± 10) × 103 kg/h from five transects on 3 days in May 2014 downwind of the Bakken shale region of North Dakota. The average emission, (28 ± 5) × 103 kg/h, extrapolates to 0.25 ± 0.05 Tg/yr, which is significantly lower than a previous estimate of CH4 emissions from northwestern North Dakota and southeastern Saskatchewan using satellite remote sensing data. We attribute the majority of CH4 emissions in the region to oil and gas operations in the Bakken based on the similarity between atmospheric C2H6 to CH4 enhancement ratios and the composition of raw natural gas withdrawn from the region.

Methane emissions from the U.S. oil and natural gas supply chain were estimated by using ground-based, facility-scale measurements and validated with aircraft observations in areas accounting for ~30% of U.S. gas production. When scaled up nationally, our facility-based estimate of 2015 supply chain emissions is 13 ± 2 teragrams per year, equivalent to 2.3% of gross U.S. gas production. This value is ~60% higher than the U.S. Environmental Protection Agency inventory estimate, likely because existing inventory methods miss emissions released during abnormal operating conditions. Methane emissions of this magnitude, per unit of natural gas consumed, produce radiative forcing over a 20-year time horizon comparable to the CO2 from natural gas combustion. Substantial emission reductions are feasible through rapid detection of the root causes of high emissions and deployment of less failure-prone systems.

We present estimates of regional methane (CH4) emissions from oil and natural gas operations in the Barnett Shale, Texas, using airborne atmospheric measurements. Using a mass balance approach on eight different flight days in March and October 2013, the total CH4 emissions for the region are estimated to be 76 ± 13 × 10(3) kg hr(-1) (equivalent to 0.66 ± 0.11 Tg CH4 yr(-1); 95% confidence interval (CI)). We estimate that 60 ± 11 × 10(3) kg CH4 hr(-1) (95% CI) are emitted by natural gas and oil operations, including production, processing, and distribution in the urban areas of Dallas and Fort Worth. This estimate agrees with the U.S. Environmental Protection Agency (EPA) estimate for nationwide CH4 emissions from the natural gas sector when scaled by natural gas production, but it is higher than emissions reported by the EDGAR inventory or by industry to EPA's Greenhouse Gas Reporting Program. This study is the first to show consistency between mass balance results on so many different days and in two different seasons, enabling better quantification of the related uncertainty. The Barnett is one of the largest production basins in the United States, with 8% of total U.S. natural gas production, and thus, our results represent a crucial step toward determining the greenhouse gas footprint of U.S. onshore natural gas production.

We present high time resolution airborne ethane (C2H6) and methane (CH4) measurements made in March and October 2013 as part of the Barnett Coordinated Campaign over the Barnett Shale formation in Texas. Ethane fluxes are quantified using a downwind flight strategy, a first demonstration of this approach for C2H6. Additionally, ethane-to-methane emissions ratios (C2H6:CH4) of point sources were observationally determined from simultaneous airborne C2H6 and CH4 measurements during a survey flight over the source region. Distinct C2H6:CH4 × 100% molar ratios of 0.0%, 1.8%, and 9.6%, indicative of microbial, low-C2H6 fossil, and high-C2H6 fossil sources, respectively, emerged in observations over the emissions source region of the Barnett Shale. Ethane-to-methane correlations were used in conjunction with C2H6 and CH4 fluxes to quantify the fraction of CH4 emissions derived from fossil and microbial sources. On the basis of two analyses, we find 71-85% of the observed methane emissions quantified in the Barnett Shale are derived from fossil sources. The average ethane flux observed from the studied region of the Barnett Shale was 6.6 ± 0.2 × 10(3) kg hr(-1) and consistent across six days in spring and fall of 2013.

The Indianapolis Flux Experiment (INFLUX) aims to develop and assess methods for quantifying urban greenhouse gas emissions. Here we use CO2, 14CO2, and CO measurements from tall towers around Indianapolis, USA, to determine urban total CO2, the fossil fuel derived CO2 component (CO2ff), and CO enhancements relative to background measurements. When a local background directly upwind of the urban area is used, the wintertime total CO2 enhancement over Indianapolis can be entirely explained by urban CO2ff emissions. Conversely, when a continental background is used, CO2ff enhancements are larger and account for only half the total CO2 enhancement, effectively representing the combined CO2ff enhancement from Indianapolis and the wider region. In summer, we find that diurnal variability in both background CO2 mole fraction and covarying vertical mixing makes it difficult to use a simple upwind-downwind difference for a reliable determination of total CO2 urban enhancement. We use characteristic CO2ff source sector CO:CO2ff emission ratios to examine the contribution of the CO2ff source sectors to total CO2ff emissions. This method is strongly sensitive to the mobile sector, which produces most CO. We show that the inventory-based emission product (“bottom up”) and atmospheric observations (“top down”) can be directly compared throughout the diurnal cycle using this ratio method. For Indianapolis, the top-down observations are consistent with the bottom-up Hestia data product emission sector patterns for most of the diurnal cycle but disagree during the nighttime hours. Further examination of both the top-down and bottom-up assumptions is needed to assess the exact cause of the discrepancy.

The identification and quantification of methane emissions from natural gas production has become increasingly important owing to the increase in the natural gas component of the energy sector. An instrumented aircraft platform was used to identify large sources of methane and quantify emission rates in southwestern PA in June 2012. A large regional flux, 2.0-14 g CH4 s(-1) km(-2), was quantified for a ∼ 2,800-km(2) area, which did not differ statistically from a bottom-up inventory, 2.3-4.6 g CH4 s(-1) km(-2). Large emissions averaging 34 g CH4/s per well were observed from seven well pads determined to be in the drilling phase, 2 to 3 orders of magnitude greater than US Environmental Protection Agency estimates for this operational phase. The emissions from these well pads, representing ∼ 1% of the total number of wells, account for 4-30% of the observed regional flux. More work is needed to determine all of the sources of methane emissions from natural gas production, to ascertain why these emissions occur and to evaluate their climate and atmospheric chemistry impacts.

[1] Methane (CH4) emissions from natural gas production are not well quantified and have the potential to offset the climate benefits of natural gas over other fossil fuels. We use atmospheric measurements in a mass balance approach to estimate CH4 emissions of 55 ± 15 × 103 kg h−1 from a natural gas and oil production field in Uintah County, Utah, on 1 day: 3 February 2012. This emission rate corresponds to 6.2%–11.7% (1σ) of average hourly natural gas production in Uintah County in the month of February. This study demonstrates the mass balance technique as a valuable tool for estimating emissions from oil and gas production regions and illustrates the need for further atmospheric measurements to determine the representativeness of our single-day estimate and to better assess inventories of CH4 emissions.

A one hour integrated flask sampling system to collect air in automated NOAA/ESRL 12-flask packages is described. The integrating compressor system uses a mass flow controller to regulate the flow of air through a 15 l volume, thus providing a mixture of air collected over an hour-long period. By beginning with a high flow rate of 3800 standard liters per minute and gradually decreasing the flow rate over time to 290 standard liters per minute it is possible to obtain a nearly uniformly time averaged sample of air and collect it into a pressurized 0.7 l flask. The weighting function determining the air mixture obtained is described in detail. Laboratory and field tests demonstrate that the integrated sample approximates a simple mean of air collected during the one-hour sampling time.

Published estimates of methane emissions from atmospheric data (top-down approaches) exceed those from source-based inventories (bottom-up approaches), leading to conflicting claims about the climate implications of fuel switching from coal or petroleum to natural gas. Based on data from a coordinated campaign in the Barnett Shale oil and gas-producing region of Texas, we find that top-down and bottom-up estimates of both total and fossil methane emissions agree within statistical confidence intervals (relative differences are 10% for fossil methane and 0.1% for total methane). We reduced uncertainty in top-down estimates by using repeated mass balance measurements, as well as ethane as a fingerprint for source attribution. Similarly, our bottom-up estimate incorporates a more complete count of facilities than past inventories, which omitted a significant number of major sources, and more effectively accounts for the influence of large emission sources using a statistical estimator that integrates observations from multiple ground-based measurement datasets. Two percent of oil and gas facilities in the Barnett accounts for half of methane emissions at any given time, and high-emitting facilities appear to be spatiotemporally variable. Measured oil and gas methane emissions are 90% larger than estimates based on the US Environmental Protection Agency’s Greenhouse Gas Inventory and correspond to 1.5% of natural gas production. This rate of methane loss increases the 20-y climate impacts of natural gas consumed in the region by roughly 50%.

Direct quantification of fossil fuel CO2 (CO2ff) in atmospheric samples can be used to examine several carbon cycle and air quality questions. We collected in situ CO2, CO, and CH4 measurements and flask samples in the boundary layer and free troposphere over Sacramento, California, USA, during two aircraft flights over and downwind of this urban area during spring of 2009. The flask samples were analyzed for Δ14CO2 and CO2 to determine the recently added CO2ff mole fraction. A suite of greenhouse and other trace gases, including hydrocarbons and halocarbons, were measured in the same samples. Strong correlations were observed between CO2ff and numerous trace gases associated with urban emissions. From these correlations we estimate emission ratios between CO2ff and these species, and compare these with bottom-up inventory-derived estimates. Recent county level inventory estimates for carbon monoxide (CO) and benzene from the California Air Resources Board CEPAM database are in good agreement with our measured emission ratios, whereas older emissions inventories appear to overestimate emissions of these gases by a factor of two. For most other trace species, there are substantial differences (200–500%) between our measured emission ratios and those derived from available emission inventories. For the first flight, we combine in situ CO measurements with the measured CO:CO2ff emission ratio of 14 ± 2 ppbCO/ppmCO2 to derive an estimate of CO2ff mole fraction throughout this flight, and also estimate the biospheric CO2 mixing ratio (CO2bio) from the difference of total and fossil CO2. The resulting CO2bio varies dramatically from up to 8 ± 2 ppm in the urban plume to −6 ± 1 ppm in the surrounding boundary layer air. Finally, we use the in situ estimates of CO2ff mole fraction to infer total fossil fuel CO2 emissions from the Sacramento region, using a mass balance approach. The resulting emissions are uncertain to within a factor of two due to uncertainties in wind speed and boundary layer height. Nevertheless, this first attempt to estimate urban-scale CO2ff from atmospheric radiocarbon measurements shows that CO2ff can be used to verify and improve emission inventories for many poorly known anthropogenic species, separate biospheric CO2, and indicates the potential to constrain CO2ff emissions if transport uncertainties are reduced.

Urban greenhouse gas (GHG) flux estimation with atmospheric measurements and modeling, i.e. the 'top-down' approach, can potentially support GHG emission reduction policies by assessing trends in surface fluxes and detecting anomalies from bottom-up inventories. Aircraft-collected GHG observations also have the potential to help quantify point-source emissions that may not be adequately sampled by fixed surface tower-based atmospheric observing systems. Here, we estimate CH4 emissions from a known point source, the Aliso Canyon natural gas leak in Los Angeles, CA from October 2015–February 2016, using atmospheric inverse models with airborne CH4 observations from twelve flights ≈4 km downwind of the leak and surface sensitivities from a mesoscale atmospheric transport model. This leak event has been well-quantified previously using various methods by the California Air Resources Board, thereby providing high confidence in the mass-balance leak rate estimates of (Conley et al 2016), used here for comparison to inversion results. Inversions with an optimal setup are shown to provide estimates of the leak magnitude, on average, within a third of the mass balance values, with remaining errors in estimated leak rates predominantly explained by modeled wind speed errors of up to 10 m s−1, quantified by comparing airborne meteorological observations with modeled values along the flight track. An inversion setup using scaled observational wind speed errors in the model-data mismatch covariance matrix is shown to significantly reduce the influence of transport model errors on spatial patterns and estimated leak rates from the inversions. In sum, this study takes advantage of a natural tracer release experiment (i.e. the Aliso Canyon natural gas leak) to identify effective approaches for reducing the influence of transport model error on atmospheric inversions of point-source emissions, while suggesting future potential for integrating surface tower and aircraft atmospheric GHG observations in top-down urban emission monitoring systems.

We report measurements of methane (CH4) emission rates observed at eight different high-emitting point sources in the Barnett Shale, Texas, using aircraft-based methods performed as part of the Barnett Coordinated Campaign. We quantified CH4 emission rates from four gas processing plants, one compressor station, and three landfills during five flights conducted in October 2013. Results are compared to other aircraft- and surface-based measurements of the same facilities, and to estimates based on a national study of gathering and processing facilities emissions and 2013 annual average emissions reported to the U.S. EPA Greenhouse Gas Reporting Program (GHGRP). For the eight sources, CH4 emission measurements from the aircraft-based mass balance approach were a factor of 3.2-5.8 greater than the GHGRP-based estimates. Summed emissions totaled 7022 ± 2000 kg hr(-1), roughly 9% of the entire basin-wide CH4 emissions estimated from regional mass balance flights during the campaign. Emission measurements from five natural gas management facilities were 1.2-4.6 times larger than emissions based on the national study. Results from this study were used to represent "super-emitters" in a newly formulated Barnett Shale Inventory, demonstrating the importance of targeted sampling of "super-emitters" that may be missed by random sampling of a subset of the total.

We report the CH4 emission flux from the city of Indianapolis, IN, the site of the Indianapolis Flux Experiment (INFLUX) project for developing, assessing, and improving top-down and bottom-up approaches for quantifying urban greenhouse gas emissions. Using an aircraft-based mass balance approach, we find that the average CH4 emission rate from five flight experiments in 2011 is 135 ± 58 (1σ) moles s-1 (7800 ± 3300 kg hr-1). The effective per capita CH4 emission rate for Indianapolis is 77 kg CH4 person-1 yr-1, a figure that is less than the national anthropogenic CH4 emission (∼91 kg CH4 person-1 yr-1) but considerably larger than the global figure (∼48 kg CH4 person-1 yr-1). We consistently observed elevated CH4 concentrations at specific coordinates along our flight transects downwind of the city. Inflight investigations as well as back trajectories using measured wind directions showed that the elevated concentrations originated from the southwest side of the city where a landfill and a natural gas transmission regulating station (TRS) are located. Street level mobile measurements downwind of the landfill and the TRS supported the results of aircraft-based data, and were used to quantify the relative contributions from the two sources. We find that the CH4 emission from the TRS was negligible relative to the landfill, which was responsible for 33 ± 10% of the citywide emission flux. A regression of propane versus methane from aircraft flask samples suggests that the remaining citywide CH4 emissions (∼67%) derive from the natural gas distribution system. We discuss the combination of surface mobile observations and aircraft city-wide flux measurements to determine the total flux and apportionment to important sources.

The current process of care transitions for individuals with disabling conditions is both ineffective and inefficient. There is a need for clinicians with the necessary knowledge and skills to advocate and facilitate transitions that result in the greatest value to the patients, their families, and the healthcare delivery system. A review of the literature reveals significant problems with transitions to postacute care (PAC) settings. Care is fragmented, disorganized, and guided by factors unrelated to the quality of care or patient outcomes. Studies have demonstrated that the selection of a PAC setting for patients is influenced by multiple factors (Sandel et al., 2009; Gage, 2009). Patients’ clinically assessed needs often do not match the level of care determined by decision makers because optimal patient outcomes may not be the primary factor considered. Competing factors include proximity of providers, relationships between providers of care, payer source, and variation in the interpretations of regulations regarding PAC. Decision makers may include the patient, family members, discharge planners, physicians, insurance company representatives, social workers, and other healthcare providers. Many times, these decision makers lack adequate information to make the best decision during care transition planning. Consequently, care transitions remain a confusing time for patients and their families and can result in both overuse and underuse of PAC services and sub-optimal quality of care and clinical outcomes. Families involved in PAC transitions often feel overwhelmed and dissatisfied (Lutz, Young, Cox, Martz, & Creasy, 2011). PAC is a significant part of the overall care of many Medicare patients. Up to 35% of Medicare patients are discharged each year to a PAC setting (Gage, 2009). Of those Medicare patients discharged, almost one-fourth of Medicare beneficiaries discharged from the hospital to a skilled nursing facility were readmitted to the hospital within 30 days (Mor, Intrator, Feng, & Grabowski, 2010). PAC is provided in various settings, including skilled nursing facilities, inpatient rehabilitation facilities, longterm care hospitals, in the home by home healthcare agencies, and outpatient centers. PAC is provided by a wide array of specialized clinicians from physical therapists, occupational therapists, physicians, speech-language pathologists, neuropsychologists, social workers, discharge planners, and nurses with and without rehabilitation expertise. Rehabilitation is a key component of the care provided in each of these settings. About 30%–60% of the older patients develop new dependence in activities of daily living (ADL) during an acute care hospital stay, which can result in progressive disability after discharge (Huang, Chang, Liu, Lin, & Chen, 2013). Determining the best setting for the patient requires a thorough understanding of rehabilitation services and evidenced-based outcomes to evaluate appropriateness of care for the patient. Pilot studies have demonstrated that when a nurse with an understanding of care transitions is integrated into the process, unplanned 30-day hospital readmission rates decline and outcomes are improved (Congressional Research Service [CRS], 2010).

Granular material flows describe flows of solid particles in which the interstitial fluid plays a negligible role in the flow mechanics. Examples include the transport of coal, food products, detergents, pharmaceutical tablets, and toner particles in high-speed printers. Using a two-dimensional discrete element computer simulation of a bounded, gravity-free Couette flow of particles, the heat dissipation rate per unit area is calculated as a function of position in the flow as well as overall solid fraction. The computation results compare favorably with the kinetic theory analysis for rough disks. The heat dissipation rate is also measured for binary mixtures of particles for different small to large solid fraction ratios, and for diameter ratios of ten, five, and two. The dissipation rates increase significantly with overall solid fraction as well as local strain rates and granular temperatures. The thermal energy equation is solved for a Couette flow with one adiabatic wall and one at constant temperature. Solutions use the simulation measurements of the heat dissipation rate, solid fraction, and granular temperature to show that the thermodynamic temperature increases with solid fraction and decreases with particle conductivity. In mixtures, both the dissipation rate and the thermodynamic temperature increase with size ratio andmore » with decreasing ratio of small to large particles.« less

[1] Atmospheric CO2 gradients are usually dominated by the signal from net terrestrial biological fluxes, despite the fact that fossil fuel combustion fluxes are larger in the annual mean. Here, we use a six year long series of 14CO2 and CO2 measurements obtained from vertical profiles at two northeast U.S. aircraft sampling sites to partition lower troposphere CO2 enhancements (and depletions) into terrestrial biological and fossil fuel components (Cbio and Cff). Mean Cff is 1.5 ppm, and 2.4 ppm when we consider only planetary boundary layer samples. However, we find that the contribution of Cbio to CO2 enhancements is large throughout the year, and averages 60% in winter. Paired observations of Cff and the lower troposphere enhancements (Δgas) of 22 other anthropogenic gases (CH4, CO, halo- and hydrocarbons and others) measured in the same samples are used to determine apparent emission ratios for each gas. We then scale these ratios by the well known U.S. fossil fuel CO2 emissions to provide observationally based estimates of national emissions for each gas and compare these to “bottom up” estimates from inventories. Correlations of Δgas with Cff for almost all gases are statistically significant with median r2for winter, summer and the entire year of 0.59, 0.45, and 0.42, respectively. Many gases exhibit statistically significant winter:summer differences in ratios that indicate seasonality of emissions or chemical destruction. The variability of ratios in a given season is not readily attributable to meteorological or geographic variables and instead most likely reflects real, short-term spatiotemporal variability of emissions.

[1] The multispecies analysis of daily air samples collected at the NOAA Boulder Atmospheric Observatory (BAO) in Weld County in northeastern Colorado since 2007 shows highly correlated alkane enhancements caused by a regionally distributed mix of sources in the Denver-Julesburg Basin. To further characterize the emissions of methane and non-methane hydrocarbons (propane, n-butane, i-pentane, n-pentane and benzene) around BAO, a pilot study involving automobile-based surveys was carried out during the summer of 2008. A mix of venting emissions (leaks) of raw natural gas and flashing emissions from condensate storage tanks can explain the alkane ratios we observe in air masses impacted by oil and gas operations in northeastern Colorado. Using the WRAP Phase III inventory of total volatile organic compound (VOC) emissions from oil and gas exploration, production and processing, together with flashing and venting emission speciation profiles provided by State agencies or the oil and gas industry, we derive a range of bottom-up speciated emissions for Weld County in 2008. We use the observed ambient molar ratios and flashing and venting emissions data to calculate top-down scenarios for the amount of natural gas leaked to the atmosphere and the associated methane and non-methane emissions. Our analysis suggests that the emissions of the species we measured are most likely underestimated in current inventories and that the uncertainties attached to these estimates can be as high as a factor of two.

The bubble flow and transom wave associated with the naval research vessel Athena I was characterized during a field experiment conducted in June 2005 by several research groups. The bubbly flow around the passing ship was documented by stationary divers using underwater cameras. The free surface behind the ship was characterized in the near field using Quantitative Visualization, a laser-imaging technique developed and used by the Naval Surface Warfare Center, Carderock Division. The far-field transom wave was quantified usin LIDAR instrumentation operated by the Scripps Institution of Oceanography. Results from the near and far-field measurements in the stern, along with images of from underwater video, are given in the report. The overall objective of the current experiment was to obtain full scale qualitative and quantitative breaking wave field data of the naval combatant surface ship for use in CFD code development and validation.

The bow wave of the R/V Athena I was quantified in calm water and in a Sea State 3 using a Quantitative Flow Visualization (QViz) system developed at the Naval Surface Warfare Center, Carderock Division. This effort represents the second time that the QViz system has been taken aboard the research vessel Athena. These experiments were performed in both the protected waters of St. Andrews Bay (Panama City, FL) and in the Gulf of Mexico. The data was collected over a five day period from May 17-21, 2004. The Athena was operated at six speeds; 2 knots (1.0m/s), 6 knots (3.1 m/s), 9 knots (4.6m/s), 10.5 knots (5.4m/s), 12 knots (6.2m/s) and 13.9 knots (7.2 m/s), corresponding to Froude numbers based on waterline length (47m) of 0.05, 0.14, 0.21, 0.24, 0.28, and 0.32 respectively. Data were collected at seven axial locations, in 1-foot (0.3m) intervals, along the bow. Predictions from the non-linear potential flow code, DAS BOOT, are compared to the experimental data. In addition to the QViz data, video cameras captured the flow around the hull at six camera locations. Additional data was obtained by other cooperating research groups and included laser altimeter measurements of the stern wake, conductivity probes to measure the void fraction in the wake of the ship, a particle/bubble imaging system to determine bubble size distributions, a defocusing bubble imaging system, and a high speed video system.

A model of the R/V Athena hull form (Model 5365) was towed on Carriage 1 of the David Taylor Model Basin at the Naval Surface Warfare Center (NSWCCD.) The R/V Athena is a converted PG-84 Asheville-class patrol gunboat. Measurements of the free-surface were made using various instrumentation systems, including conductivity probes in the stern region, Quantitative Visualization in the bow and shoulder wave region, and wave capacitance probes for stationary measurements of the transverse wave field. Video cameras were also used to qualitatively characterize the wave field and compare it with video of the full-scale vessel.

A prismatic wedge was towed in fresh water in the David Taylor Model Basin at the Naval Surface Warfare Center, Carderock Division (NSWCCD), generating a large bow wave. Towing speeds ranged from 0.7 to 4.6 m/s, and drafts ranged from 0.6 to 1.5 m. These conditions correspond to Froude numbers from 0.2 to 1.4, Reynolds numbers from 4.1 xl0(exp 5) to 7.0x10(exp 6) (both based on draft, D) and Weber numbers from 11 to 2800 (based on bow radius, R). In addition to the variations in draft and speed, two different bow geometries were investigated: one with a 20 degree bow entrance angle, 20 degree flare, and sharp leading edge, and one with a 40 degree bow entrance angle, no flare, and rounded leading edge. Measurements of free-surface elevations near the bow were made using a laser imaging technique. High-speed video of the spray generated by the bow wave was also analyzed to yield droplet size and velocity distributions. These measurements provide a useful data set to researchers wishing to validate advanced numerical techniques. Presently, the results are used to investigate scaling issues associated with breaking bow waves.