Chamber Data Research Articles

Tuning the genie pion production model with MINERvA data

Faced with unresolved tensions between neutrino interaction measurements at few-GeV neutrino energies, current experiments are forced to accept large systematic uncertainties to cover discrepancies between their data and model predictions. In this paper, the widely used pion production model in GENIE is compared to four MINERvA charged current pion production measurements using NUISANCE. Tunings, ie, adjustments of model parameters, to help match GENIE to MINERvA and older bubble chamber data are presented here. We find that scattering off nuclear targets as measured in MINERvA is not in good agreement with scattering off nucleon (hydrogen or deuterium) targets in the bubble chamber data. An additional ad hoc correction for the low-$Q^2$ region, where collective effects are expected to be large, is also presented. While these tunings and corrections improve the agreement of GENIE with the data, the modeling is imperfect. The development of these tunings within the NUISANCE frameworkallows for straightforward extensions to other neutrino event generators and models, and allows omitting and including new data sets as they become available.

Secondary organic aerosol formation from smoldering and flaming combustion of biomass: a box model parametrization based on volatility basis set

Abstract. Residential wood combustion remains one of the most important sources of primary organic aerosols (POA) and secondary organic aerosol (SOA) precursors during winter. The overwhelming majority of these precursors have not been traditionally considered in regional models, and only recently were lignin pyrolysis products and polycyclic aromatics identified as the principal SOA precursors from flaming wood combustion. The SOA yields of these components in the complex matrix of biomass smoke remain unknown and may not be inferred from smog chamber data based on single-compound systems. Here, we studied the ageing of emissions from flaming and smoldering-dominated wood fires in three different residential stoves, across a wide range of ageing temperatures (−10, 2 and 15 ∘C) and emission loads. Organic gases (OGs) acting as SOA precursors were monitored by a proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS), while the evolution of the aerosol properties during ageing in the smog chamber was monitored by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). We developed a novel box model based on the volatility basis set (VBS) to determine the volatility distributions of the oxidation products from different precursor classes found in the emissions, grouped according to their emission pathways and SOA production rates. We show for the first time that SOA yields in complex emissions are consistent with those reported in literature from single-compound systems. We identify the main SOA precursors in both flaming and smoldering wood combustion emissions at different temperatures. While single-ring and polycyclic aromatics are significant precursors in flaming emissions, furans generated from cellulose pyrolysis appear to be important for SOA production in the case of smoldering fires. This is especially the case at high loads and low temperatures, given the higher volatility of furan oxidation products predicted by the model. We show that the oxidation products of oxygenated aromatics from lignin pyrolysis are expected to dominate SOA formation, independent of the combustion or ageing conditions, and therefore can be used as promising markers to trace ageing of biomass smoke in the field. The model framework developed herein may be generalizable for other complex emission sources, allowing determination of the contributions of different precursor classes to SOA, at a level of complexity suitable for implementation in regional air quality models.

Wireless Stretchable Hybrid Electronics for Smart, Connected, and Ambulatory Monitoring of Human Health

Continuous ambulatory cardiac monitoring using electrocardiogram (ECG) can reveal a range of essential health conditions. However, commercially available devices rely on bulky wires, rigid sensors/electronics and cause great discomfort that disrupts one’s lifestyle and prevents long-term use. Moreover, standard gel-based electrodes are prone to degradation over long-term use and can causing allergic skin reactions. Also, research-level skin-wearable devices, while excelling in few aspects, fall short as concept-only presentations, due to the fundamental challenges in active wireless communication and integration as a single device platform. Here, we introduce a fully wireless, low-profile, multifunctional stretchable hybrid electronic (SHE) device that offers smart, connected, and ambulatory health monitoring. As shown in Figure 1, the low-modulus, elastomeric system construction provides the gentle, yet sufficient, device adhesion to skin, obviating the need for straps, tapes, or adhesives, and demonstrates a type of monitoring scheme inconspicuous not only to the observer, but also to the user. Integration of a set of stretchable nanomembrane sensors with a highly flexible, membrane-based wireless circuit enables the continuous, long-range (up to 15 m) monitoring of ECG, heart rate, respiratory rate, and physical activities. Implementation of convolutional neural networks and algorithms for real-time classifications of multi-modal physiological signals demonstrates the device feasibility for multi-faceted clinically relevant analysis. In vivo demonstrations involving human subjects both with and without cardiac conditions reveal the feasibility of the device as a continuous, ambulatory, and multifunctional health monitor with emphasis on real-time detection of cardiac abnormalities. Further in vivo demonstration of SHE applied on athletes during treadmill exercises validate the versatility of SHE in both clinical and research environments. Figure 1: Overview of SHE. (A) Photograph showing the stretchable hybrid electronics applied on human chest. (B) Blow-up render detailing the structural components of SHE including the thin-film stretchable skin electrodes, hyperelastic membranes, mechanical decoupling chamber, stretchable connector, and flexible data acquisition unit. Figure 1

Online Fault Detection and Isolation in Advanced Heavy Water Reactor Using Multiscale Principal Component Analysis

Signals from sensors placed at different locations are used for control and protection purposes in a nuclear reactor. It also requires in-service fault detection and isolation (FDI) for its safe operation. The sensor signals are generally a superimposition of low-frequency components representative of true values of the variables being monitored, occasional high-frequency periodical oscillations due to disturbances and faults, and sensor faults. Techniques like principal component analysis (PCA) can be used for FDI; however, it would be more meaningful if the FDI technique can also help for predictive maintenance of reactor internals through vibration spectra. To address these issues, a multiscale PCA, integrating wavelet transform with PCA and aiming to reduce the modeling cost by using only a fewer scales that contribute to the monitoring, has been proposed in this paper for online FDI of an advanced heavy water reactor (AHWR). A new mathematical formulation of the generalized likelihood ratio test for its use with wavelet approximation coefficients has also been proposed for better sensor-FDI outcomes. The proposed approach detects and isolates sensor faults and process faults using the signals from neutron detectors. Efficacy of the proposed technique is established on the simulated ex-core ion chamber data of AHWR considering different scenarios that involve localized frequency contents representative of process faults, slowly developing (incipient) sensor faults, and the simultaneous presence of two or more of these scenarios. Simulation results validate the effectiveness of the proposed scheme for online FDI in the reactor.

On Calculating Deposition Coefficients and Aspect-Ratio Evolution in Approximate Models of Ice Crystal Vapor Growth

AbstractModels of ice crystal vapor growth require estimates of the deposition coefficient α when surface attachment kinetics limit growth and when ice crystal shape is predicted. Parametric models can be used to calculate α for faceted growth as long as characteristic supersaturation values are known. However, previously published measurements of are limited to temperatures higher than −40°C. Estimates of at temperatures between −40° and −70°C are provided here through reanalysis of vapor growth data. The estimated follow the same functional temperature dependence as data taken at higher temperatures. Polynomial fits to are used as inputs to a parameterization of α suitable for use in cloud models. Comparisons of the parameterization with wind tunnel data show that growth at liquid saturation and constant temperatures between −3° and −20°C can be modeled by ledge nucleation for larger (hundreds of micrometers) crystals; however, comparisons with free-fall chamber data at −7°C suggest that dislocation growth may be required to model the vapor growth of small crystals (~20 μm) at liquid saturation. The comparisons with free-fall chamber data also show that the parameterization can reproduce the measured pressure dependence of aspect-ratio evolution. Comparisons with a hexagonal growth model indicate that aspect-ratio evolution based on the theory of Chen and Lamb produces unrealistically fast column growth near −7°C that is mitigated if a theory based on faceted growth is used. This result indicates that the growth hypothesis used in habit-evolving microphysical models needs to be revised when deposition coefficients are predicted.

Carbon exchange in a hemiboreal mixed forest in relation to tree species composition

Hemiboreal forests form a transitional belt between boreal and temperate forests in Eurasia, and due to long-term climate warming they could potentially expand in a northerly direction. However, carbon (C) exchange studies in this transitional forest type are scarce. In 2014–2015 we analyzed CO2 exchange in a hemiboreal mixed forest at SMEAR Estonia (Station for Measuring Ecosystem-Atmosphere Relations) using eddy covariance (EC), soil chamber technique and biometric methods. Employing two plots that differ in forest stand composition (mixed (MP) and coniferous (CP)) located within the footprint of the EC tower, we evaluated heterotrophic and total soil respiration (Rh and Rs, respectively). Measurements showed that C, nitrogen (N), and soil organic matter (SOM) contents in topsoil were significantly higher in the coniferous plot, and the total C stock until 20 cm of mineral soil was higher by a factor of two (i.e., 170.6 and 94.8 t C ha−1 for the CP and MP, respectively). Only in 2015 there was a significant difference in Rs between the plots, while Rh exhibited no detectable difference. The cumulative Rs during the growing season was similar for both plots (CP and MP) and years: 532 and 548 g m−2, respectively, in 2014; 636 and 592 g m−2, respectively, in 2015. The same applied to Rh: 418 and 430 g m−2, respectively, in 2014; 406 and 387 g m−2, respectively, in 2015.The forest as a whole was a C sink. In 2015, net ecosystem exchange (NEE) was -585.62 ± 45.16 g C m−2 yr−1 (the average and SD of two gap-filling methods: MDS and nonlinear regressions). Gross primary production (GPP), and ecosystem respiration (RE) were -1280.62 ± 53.36, and 696.00 ± 98.51 g C m−2 yr−1, respectively (the average and SD of two flux partitioning methods: nighttime data-based and daytime data-based). NEE and GPP suggested a greater similarity to temperate forests, while RE was closer to more boreal forest stands.The mean value of net ecosystem production (NEP) of both plots, estimated using forest stand biometric, litter and chamber data was similar to the annual NEE value: 6.3 and −5.9 t C ha−1 yr−1, respectively.

Application of Bayesian statistics to estimate nitrous oxide emission factors of three nitrogen fertilisers on UK grasslands

Trapezoidal integration by linear interpolation of data points is by far the most commonly used method of cumulative flux calculations of nitrous oxide (N2O) in studies that use flux chambers; however, this method is incapable of providing accurate uncertainty estimates. A Bayesian approach was used to calculate N2O emission factors (EFs) and their associated uncertainties from flux chamber measurements made after the application of nitrogen fertilisers, in the form of ammonium nitrate (AN), urea (Ur) and urea treated with Agrotain® urease inhibitor (UI) at four grassland sites in the UK. The comparison between the cumulative fluxes estimated using the Bayesian and linear interpolation methods were broadly similar (R2 = 0.79); however, the Bayesian method was capable of providing realistic uncertainties when a limited number of data points is available. The study reports mean EF values (and 95% confidence intervals) of 0.60 ± 0.63, 0.29 ± 0.22 and 0.26 ± 0.17% of applied N emitted as N2O for the AN, Ur and UI treatments, respectively. There was no significant difference between N2O emissions from the Ur and UI treatments. In the case of the automatic chamber data collected at one site in this study, the data did not fit the log-normal model, implying that more complex models may be needed, particularly for measurement data with high temporal resolution.

Sediment Oxygen Demand: A Review of In Situ Methods

Sediment oxygen demand (SOD) plays a fundamental role in biological and chemical processes within the benthic layer of a water body. Land use, including agricultural land use, can affect SOD. However, a wide variety of approaches have been used for in situ SOD chamber construction and data collection, and modelers frequently use SOD values from the literature, without consideration of the differences in methods. Here, we review existing literature on SOD chambers (32 papers, 1974-2016), compare the differences between in situ and laboratory methods, evaluate the effects of in situ chamber mixing, and discuss common challenges associated with deployment. A cohesive in situ sealed chamber design for use with a multiparameter water-quality instrument is presented as an effort toward standardizing SOD methodology, an important consideration that may facilitate integration of SOD data sets among multiple research efforts.

Impact of final state interactions on neutrino-nucleon pion production cross sections extracted from neutrino-deuteron reaction data

The current and near-future neutrino oscillation experiments require significantly improved neutrino-nucleus reaction models. Neutrino-nucleon pion production data play a crucial role to validate corresponding elementary amplitudes that go into such neutrino-nucleus models. Thus the currently available data extracted from charged-current neutrino-deuteron reaction data ($\nu_\mu d\to \mu^-\pi NN$) must be corrected for nuclear effects such as the Fermi motion and final state interactions (FSI). We study $\nu_\mu d\to \mu^-\pi NN$ with a theoretical model including the impulse mechanism supplemented by FSI from $NN$ and $\pi N$ rescatterings. An analysis of the spectator momentum distributions reveals that the FSI effects significantly reduce the spectra over the quasi-free peak region, and leads to a useful recipe to extract information of elementary $\nu_\mu N\to \mu^-\pi N$ processes using $\nu_\mu d\to \mu^-\pi NN$ data, with the important FSI corrections taken into account. We provide $\nu_\mu N\to \mu^-\pi N$ total cross sections by correcting the deuterium bubble chamber data for the FSI and Fermi motion. The results will bring a significant improvement on neutrino-nucleus reaction models for the near-future neutrino-oscillation experiments.

Environmental and Vegetative Controls on Soil CO2 Efflux in Three Semiarid Ecosystems

Soil CO2 efflux (Fsoil) is a major component of the ecosystem carbon balance. Globally expansive semiarid ecosystems have been shown to influence the trend and interannual variability of the terrestrial carbon sink. Modeling Fsoil in water-limited ecosystems remains relatively difficult due to high spatial and temporal variability associated with dynamics in moisture availability and biological activity. Measurements of the processes underlying variability in Fsoil can help evaluate Fsoil models for water-limited ecosystems. Here we combine automated soil chamber and flux tower data with models to investigate how soil temperature (Ts), soil moisture (θ), and gross ecosystem photosynthesis (GEP) control Fsoil in semiarid ecosystems with similar climates and different vegetation types. Across grassland, shrubland, and savanna sites, θ regulated the relationship between Fsoil and Ts, and GEP influenced Fsoil magnitude. Thus, the combination of Ts, θ, and GEP controlled rates and patterns of Fsoil. In a root exclusion experiment at the grassland, we found that growing season autotrophic respiration accounted for 45% of Fsoil. Our modeling results indicate that a combination of Ts, θ, and GEP terms is required to model spatial and temporal dynamics in Fsoil, particularly in deeper-rooted shrublands and savannas where coupling between GEP and shallow θ is weaker than in grasslands. Together, these results highlight that including θ and GEP in Fsoil models can help reduce uncertainty in semiarid ecosystem carbon dynamics.

Demonstration of MeV-scale physics in liquid argon time projection chambers using ArgoNeuT

MeV-scale energy depositions by low-energy photons produced in neutrino-argon interactions have been identified and reconstructed in ArgoNeuT liquid argon time projection chamber (LArTPC) data. ArgoNeuT data collected on the NuMI beam at Fermilab were analyzed to select isolated low-energy depositions in the TPC volume. The total number, reconstructed energies and positions of these depositions have been compared to those from simulations of neutrino-argon interactions using the FLUKA Monte Carlo generator. Measured features are consistent with energy depositions from photons produced by de-excitation of the neutrino's target nucleus and by inelastic scattering of primary neutrons produced by neutrino-argon interactions. This study represents a successful reconstruction of physics at the MeV-scale in a LArTPC, a capability of crucial importance for detection and reconstruction of supernova and solar neutrino interactions in future large LArTPCs.

Simulasi Perpindahan Panas Pada Heater Injection Molding Menggunakan Software Solidworks

Plastic is a material that takes several years to decompose, so a recycling device such as an injection molding machine is needed. This injection molding is very good at managing useless plastic waste items that are worth the sale price. The purpose of this simulation analysis with solidworks software is to design the injection chamber and analyze it to get good results, so that there are no losses in making the engine later. Based on simulation data analysis is done by varying the heating temperature. Under heating conditions 150 ℃ the highest temperature distribution is 150 ℃ and the lowest is 146,196 ℃ with the lowest Heat flux 2,554,494 W / m ^ 2 and the highest Heat flux is 29,984.35 W / m ^ 2. Under heating conditions 200 ℃ the highest temperature distribution 150 ℃ and the lowest 194.611 ℃ with the lowest Heat flux 3,618,867 W / m ^ 2 and the highest Heat flux 42,477,828 W / m ^ 2. Under heating conditions 250 ℃ the highest temperature distribution of 150 ℃ and the lowest 243,027 ℃ with the lowest heat flux 4,683.24 W / m ^ 2 and the highest Heat flux 54,971,131 W / m ^ 2. From the analysis of injection chamber data the results are at a heating temperature of 150 ℃ producing a heat capacity of 41.99 KJ while at a heating temperature of 200 ℃ it produces a heat capacity of 59.49 KJ and at a heating temperature of 250 ℃ produces a heat capacity of 76.99 KJ.

Ammonia Emissions from Subalpine Forest and Mountain Grassland Soils in Rocky Mountain National Park.

Atmospheric deposition of NH and NH contributes to eutrophication within sensitive subalpine ecosystems of Rocky Mountain National Park (RMNP) in the United States. However, little is known about the local contribution of NH from soils within the park. Thus, the goal of this study was to quantify and compare NH emissions from intact soil cores sampled from a subalpine grassland and forest within RMNP. Cores were collected at 2-wk intervals from 20 June 2011 to 12 Sept. 2011 and transferred to a laboratory chamber system for NH flux measurements. Additionally, N wet deposition was monitored at the sampling location to investigate possible impacts on NH soil emissions. The average quantifiable NH emissions (with SDs) from intact soil cores analyzed in the laboratory (23°C) were 0.42 ± 0.30 mg NH-N m d for grassland soil and 0.21 ± 0.03 mg NH-N m d for forest soil ( < 0.001). A mechanistic model was developed to estimate the impact of temperature on soil emissions using the chamber data and field-site air temperatures. Average estimated NH emissions from the field site over the study period were 0.21 and 0.082 mg NH-N m d for grasslands and forests, respectively. Ammonium wet deposition was not correlated to short term reemission of NH based on N isotope analysis. This work provides new information on the magnitude of NH emissions from native subalpine soils, indicating that natural emissions are not likely major sources of NH in the RMNP airshed.

Temporal Variation of Ecosystem Scale Methane Emission From a Boreal Fen in Relation to Temperature, Water Table Position, and Carbon Dioxide Fluxes

AbstractWe have analyzed decade‐long methane flux data set from a boreal fen, Siikaneva, together with data on environmental parameters and carbon dioxide exchange. The methane flux showed seasonal cycle but no systematic diel cycle. The highest fluxes were observed in July–August with average value of 73 nmol m−2 s−1. Wintertime fluxes were small but positive, with January–March average of 6.7 nmol m−2 s−1. Daily average methane emission correlated best with peat temperatures at 20–35 cm depths. The second highest correlation was with gross primary production (GPP). The best correspondence between emission algorithm and measured fluxes was found for a variable‐slope generalized linear model (r2 = 0.89) with peat temperature at 35 cm depth and GPP as explanatory variables, slopes varying between years. The homogeneity of slope approach indicated that seasonal variation explained 79% of the sum of squares variation of daily average methane emission, the interannual variation in explanatory factors 7.0%, functional change 5.3%, and random variation 9.1%. Significant correlation between interannual variability of growing season methane emission and that of GPP indicates that on interannual time scales GPP controls methane emission variability, crucially for development of process‐based methane emission models. Annual methane emission ranged from 6.0 to 14 gC m−2 and was 2.7 ± 0.4% of annual GPP. Over 10‐year period methane emission was 18% of net ecosystem exchange as carbon. The weak relation of methane emission to water table position indicates that space‐to‐time analogy, used to extrapolate spatial chamber data in time, may not be applicable in seasonal time scales.

Remote Cherenkov imaging-based quality assurance of a magnetic resonance image-guided radiotherapy system.

Tools to perform regular quality assurance of magnetic resonance image-guided radiotherapy (MRIgRT) systems should ideally be independent of interference from the magnetic fields. Remotely acquired optical Cherenkov imaging-based dosimetry measurements in water were investigated for this purpose, comparing measures of dose accuracy, temporal dynamics, and overall integrated IMRT delivery. A 40×30.5×37.5cm3 water tank doped with 1g/L of quinine sulfate was imaged using an intensified charge-coupled device (ICCD) to capture the Cherenkov emission while being irradiated by a commercial MRIgRT system (ViewRay™). The ICCD was placed down-bore at the end of the couch, 4m from treatment isocenter and behind the 5-Gauss line of the 0.35-T MRI. After establishing optimal camera acquisition settings, square beams of increasing size (4.2×4.2cm2 , 10.5×10.5cm2 , and 14.7×14.7cm2 ) were imaged at 0.93 frames per second, from an individual cobalt-60 treatment head, to develop projection measures related to percent depth dose (PDD) curves and cross beam profiles (CPB). These Cherenkov-derived measurements were compared to ionization chamber (IC) and radiographic film dosimetry data, as well as simulation data from the treatment planning system (TPS). An intensity-modulated radiotherapy (IMRT) commissioning plan from AAPM TG-119 (C4:C-Shape) was also imaged at 2.1 frames per second, and the single linear sum image from 509s of plan delivery was compared to the dose volume prediction generated by the TPS using gamma index analysis. Analysis of standardized test target images (1024×1024pixels) yielded a pixel resolution of 0.37mm/pixel. The beam width measured from the Cherenkov image-generated projection CBPs was within 1mm accuracy when compared to film measurements for all beams. The 502 point measurements (i.e., pixels) of the Cherenkov image-based projection percent depth dose curves (pPDDs) were compared to pPDDs simulated by the treatment planning system (TPS), with an overall average error of 0.60%, 0.56%, and 0.65% for the 4.2, 10.5, and 14.7cm square beams, respectively. The relationships between pPDDs and central axis PDDs derived from the TPS were used to apply a weighting factor to the Cherenkov pPDD, so that the Cherenkov data could be directly compared to IC PDDs (average error of -0.07%, 0.10%, and -0.01% for the same sized beams, respectively). Finally, the composite image of the TG-119 C4 treatment plan achieved a 95.1% passing rate using 4%/4mm gamma index agreement criteria between Cherenkov intensity and TPS dose volume data. This is the first examination of Cherenkov-generated pPDDs and pCBPs in an MR-IGRT system. Cherenkov imaging measurements were fast to acquire, and minimal error was observed overall. Cherenkov imaging also provided novel real-time data for IMRT QA. The strengths of this imaging are the rapid data capture ability providing real-time, high spatial resolution data, combined with the remote, noncontact nature of imaging. The biggest limitation of this method is the two-dimensional (2D) projection-based imaging of three-dimensional (3D) dose distributions through the transparent water tank.

Depth Dose Measurement using a Scintillating Fiber Optic Dosimeter for Proton Therapy Beam of the Passive-Scattering Mode Having Range Modulator Wheel

To apply a scintillating fiber dosimetry system to measure the range of a proton therapy beam, a new method was proposed to correct for the quenching effect on measuring an spread out Bragg peak (SOBP) proton beam whose range is modulated by a range modulator wheel. The scintillating fiber dosimetry system was composed of a plastic scintillating fiber (BCF-12), optical fiber (SH 2001), photo multiplier tube (H7546), and data acquisition system (PXI6221 and SCC68). The proton beam was generated by a cyclotron (Proteus-235) in the National Cancer Center in Korea. It operated in the double-scattering mode and the spread out of the Bragg peak was achieved by a spinning range modulation wheel. Bragg peak beams and SOBP beams of various ranges were measured, corrected, and compared to the ion chamber data. For the Bragg peak beam, quenching equation was used to correct the quenching effect. On the proposed process of correcting SOBP beams, the measured data using a scintillating fiber were separated by the Bragg peaks that the SOBP beam contained, and then recomposed again to reconstruct an SOBP after correcting for each Bragg peak. The measured depth-dose curve for the single Bragg peak beam was well corrected by using a simple quenching equation. Correction for SOBP beam was conducted with a newly proposed method. The corrected SOBP signal was in accordance with the results measured with an ion chamber. We propose a new method to correct for the SOBP beam from the quenching effect in a scintillating fiber dosimetry system. This method can be applied to other scintillator dosimetry for radiation beams in which the quenching effect is shown in the scintillator.

Potential for negative emissions of greenhouse gases (CO2, CH4 and N2O) through coastal peatland re-establishment: Novel insights from high frequency flux data at meter and kilometer scales

High productivity temperate wetlands that accrete peat via belowground biomass (peatlands) may be managed for climate mitigation benefits due to their global distribution and notably negative emissions of atmospheric carbon dioxide (CO2) through rapid storage of carbon (C) in anoxic soils. Net emissions of additional greenhouse gases (GHG)—methane (CH4) and nitrous oxide (N2O)—are more difficult to predict and monitor due to fine-scale temporal and spatial variability, but can potentially reverse the climate mitigation benefits resulting from CO2 uptake. To support management decisions and modeling, we collected continuous 96 hour high frequency GHG flux data for CO2, CH4 and N2O at multiple scales—static chambers (1 Hz) and eddy covariance (10 Hz)—during peak productivity in a well-studied, impounded coastal peatland in California’s Sacramento Delta with high annual rates of C fluxes, sequestering 2065 ± 150 g CO2 m−2 y−1 and emitting 64.5 ± 2.4 g CH4 m−2 y−1. Chambers (n = 6) showed strong spatial variability along a hydrologic gradient from inlet to interior plots. Daily (24 hour) net CO2 uptake (NEE) was highest near inlet locations and fell dramatically along the flowpath (−25 to −3.8 to +2.64 g CO2 m−2 d−1). In contrast, daily net CH4 flux increased along the flowpath (0.39 to 0.62 to 0.88 g CH4 m−2 d−1), such that sites of high daily CO2 uptake were sites of low CH4 emission. Distributed, continuous chamber data exposed five novel insights, and at least two important datagaps for wetland GHG management, including: (1) increasing dominance of CH4 ebullition fluxes (15%–32% of total) along the flowpath and (2) net negative N2O flux across all sites as measured during a 4 day period of peak biomass (−1.7 mg N2O m−2 d−1; 0.51 g CO2 eq m−2 d−1). The net negative emissions of re-established peat-accreting wetlands are notably high, but may be poorly estimated by models that do not consider within-wetland spatial variability due to water flowpaths.

Seasonal and inter-annual variability of soil CO2 efflux in a Norway spruce forest over an eight-year study

Automated soil CO2 efflux chamber measurements were carried out over a period of eight years in a young Norway spruce forest in the northeast region of the Czech Republic to determine seasonal and inter-annual variables affecting this flux. The data obtained was summarized and analysed with the aims of estimating long-term carbon losses from the soil and comparing selected models to determine the model best describing soil CO2 efflux. Our results show that seasonal variation in soil CO2 efflux was driven mainly by soil temperature, while inter-annual variation showed the closest relationship with precipitation. The total amount of carbon released from the soil into the atmosphere per season varied from 6.4 to 11.2 tC ha−1 over the eight-year record. One of the variables used in the CO2 efflux models, beside environmental variables, was day of year (DOY). Incorporating this variable into models improved the estimation of soil CO2 efflux dynamics. Therefore, we assume that models incorporating DOY could be used effectively to gap-fill measured soil chamber data. These models could also be appropriate for filling longer gaps on a scale from days to weeks, because DOY, as a single parameter, covers up to 80% of variability in the data. This study also demonstrated the different levels of correlation between investigated climate variables and soil CO2 efflux at seasonal and inter-annual time scales. This highlights the importance of different environmental variables in interpreting long-term soil CO2 efflux data and also modelling the complexity of the processes connected with soil CO2 efflux in Norway spruce forest.

Evaluation of Different Gases and Gas Combinations for On-Farm Euthanasia of Pre-Weaned Pigs.

Simple SummaryThere are times on a swine farm when pigs become ill or injured and must be euthanised. Blunt force trauma to the head is currently the most commonly employed method for on-farm euthanasia of pre-weaned piglets. When performed correctly, loss of consciousness is rapid, but the potential for delivery of sub-lethal blows, along with aesthetic unacceptability to many operators, has led to the need for alternative methods to be developed. The practice of using carbon dioxide (CO2) to euthanise piglets during the pre-weaning period is becoming more common on-farm in the United States; however, animals may display behavioural and/or physiological signs of stress or aversion in response to CO2 inhalation. Inducing anoxia using argon (Ar) gas may cause less aversion or stress and thus be preferable to using CO2. Therefore, the aim of this research was to evaluate the effects of 100% CO2, 100% Ar or CO2 and Ar combined (60% Ar/40% CO2) on piglet welfare during euthanasia. The results from this research suggest that using CO2, Ar or a 60% Ar/40% CO2 mixture causes stress to piglets prior to loss of consciousness and hence alternative methods of euthanasia need to be evaluated.The aim of this research was to evaluate the welfare of pre-weaned piglets euthanised using three different gas treatments: 100% carbon dioxide (CO2), 100% argon (Ar) or a mixture of 60% Ar/40% carbon dioxide (Ar/CO2). Two studies (n = 5 piglets/treatment/study) were conducted: (1) behavioural and physiological data were collected from conscious piglets during exposure to test gases via immersion in a pre-filled chamber and (2) electrophysiological data were collected from lightly anaesthetised, intubated and mechanically ventilated piglets exposed to the same test gases. Based on the duration of escape attempts and laboured breathing, piglets exposed to 100% CO2 experienced more stress than piglets exposed to 100% Ar prior to loss of consciousness, but there appeared to be no advantage of mixing Ar with CO2 on indices of animal welfare. However, spectral analysis of the electroencephalogram revealed no changes consistent with nociception during exposure to any of the three gas treatments. Based on the behavioural response to gas exposure, all gases tested caused signs of stress prior to piglets losing consciousness and hence alternative methods of euthanasia need to be evaluated.

Phenomenological study of the pp→π+pn reaction

Fully constrained bubble chamber data on the pp -> pi+ pn and pp -> pi+ d reactions are used to investigate the ratio of the counting rates for the two processes as function of the pn excitation energy Q. Though it is important to include effects associated with the p-wave nature of pion production, the data are insufficient to establish unambiguously the dependence on Q. The angular distributions show the presence of higher partial waves which seem to be anomalously large at small Q. The dispersion relation method to determine scattering lengths is extended to encompass cases where, as for the pp -> pi+ pn reaction, there is a bound state and, in a test example, it is shown that the values deduced for the low energy neutron-proton scattering parameters are significantly influenced by the pion p-wave behavior.