160 research outputs found

    Nitrous oxide emissions from 2008 to 2012 for agricultural lands in the conterminous United States

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    The soil N2O emissions data for the conterminous United States were generated by the DayCent ecosystem model using the crop and land-use histories for survey locations in the USDA-NRCS National Resources Inventory (NRI). The model also requires weather and soils data. Daily maximum/minimum temperature and precipitation data are based on gridded weather data from the PRISM Climate Data product. Soils data are obtained from Soil Survey Geographic Database (SSURGO). See Del Grosso et al. (2022) and US-EPA (2020) for more details about the simulations. Atmospheric inversions were conducted using the CarbonTracker Langrage framework (Nevison et al. 2018). These results provide total N2O fluxes for the domain using atmospheric observations and an inverse modeling, and are compared to the DayCent emissions to confirm seasonal patterns, particularly the role of freeze-thaw events in driving pulses of N2O emissions from agricultural lands.Nitrous oxide (N2O) is an important greenhouse gas (GHG) that also contributes to depletion of ozone in the stratosphere. Agricultural soils account for about 60% of anthropogenic N2O emissions. Most national GHG reporting to the UN Framework Convention on Climate Change assumes nitrogen (N) additions drive emissions during the growing season, but soil freezing and thawing during spring is also an important driver in cold climates. We show that both atmospheric inversions and newly implemented bottom-up modeling approaches exhibit large N2O pulses in the northcentral region of the United States during early spring and this increases annual N2O emissions from croplands and grasslands reported in the national GHG inventory by 11%. Considering this, emission accounting in cold climate regions is very likely under-estimated in most national reporting frameworks. Current commitments related to the Paris Agreement and COP 26 emphasize reductions of carbon compounds. Assuming these targets are met, the importance of accurately accounting and mitigating N2O increases once CO2 and CH4 are phased out. Hence, the N2O emission under-estimate introduces additional risks into meeting long term climate goals.US Forest Service 18-CR-11242305-109, US Department of Agriculture (USDA) UV-B Monitoring and Research Program, Colorado State University, under USDA National Institute of Food and Agriculture Grant 2016-34263-25763, and the USDA GHG and DayCent modeling NACA agreements (58-3012-9-012 and 58-3012-1-015

    Impact of variable air-sea O2 and CO2 fluxes on atmospheric potential oxygen (APO) and land-ocean carbon sink partitioning

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    © 2008 Author(s). This article is distributed under the terms of the Creative Commons Attribution 3.0 License. The definitive version was published in Biogeosciences 5 (2008): 875-899, doi:10.5194/bg-5-875-2008A three dimensional, time-evolving field of atmospheric potential oxygen (APO ~O2/N2+CO2) was estimated using surface O2, N2 and CO2 fluxes from the WHOI ocean ecosystem model to force the MATCH atmospheric transport model. Land and fossil carbon fluxes were also run in MATCH and translated into O2 tracers using assumed O2:CO2 stoichiometries. The modeled seasonal cycles in APO agree well with the observed cycles at 13 global monitoring stations, with agreement helped by including oceanic CO2 in the APO calculation. The modeled latitudinal gradient in APO is strongly influenced by seasonal rectifier effects in atmospheric transport. An analysis of the APO-vs.-CO2 mass-balance method for partitioning land and ocean carbon sinks was performed in the controlled context of the MATCH simulation, in which the true surface carbon and oxygen fluxes were known exactly. This analysis suggests uncertainty of up to ±0.2 PgC in the inferred sinks due to variability associated with sparse atmospheric sampling. It also shows that interannual variability in oceanic O2 fluxes can cause large errors in the sink partitioning when the method is applied over short timescales. However, when decadal or longer averages are used, the variability in the oceanic O2 flux is relatively small, allowing carbon sinks to be partitioned to within a standard deviation of 0.1 Pg C/yr of the true values, provided one has an accurate estimate of long-term mean O2 outgassing.We acknowledge the support of NASA grant NNG05GG30G and NSF grant ATM0628472

    Evaluating CMIP5 ocean biogeochemistry and Southern Ocean carbon uptake using atmospheric potential oxygen: Present-day performance and future projection

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    Observed seasonal cycles in atmospheric potential oxygen (APO ~ O2 + 1.1 CO2) were used to evaluate eight ocean biogeochemistry models from the Coupled Model Intercomparison Project (CMIP5). Model APO seasonal cycles were computed from the CMIP5 air-sea O2 and CO2 fluxes and compared to observations at three Southern Hemisphere monitoring sites. Four of the models captured either the observed APO seasonal amplitude or phasing relatively well, while the other four did not. Many models had an unrealistic seasonal phasing or amplitude of the CO2 flux, which in turn influenced APO. By 2100 under RCP8.5, the models projected little change in the O2 component of APO but large changes in the seasonality of the CO2 component associated with ocean acidification. The models with poorer performance on present-day APO tended to project larger net carbon uptake in the Southern Ocean, both today and in 2100

    Learning Mazes with Aliasing States: An LCS Algorithm with Associative Perception

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    Learning classifier systems (LCSs) belong to a class of algorithms based on the principle of self-organization and have frequently been applied to the task of solving mazes, an important type of reinforcement learning (RL) problem. Maze problems represent a simplified virtual model of real environments that can be used for developing core algorithms of many real-world applications related to the problem of navigation. However, the best achievements of LCSs in maze problems are still mostly bounded to non-aliasing environments, while LCS complexity seems to obstruct a proper analysis of the reasons of failure. We construct a new LCS agent that has a simpler and more transparent performance mechanism, but that can still solve mazes better than existing algorithms. We use the structure of a predictive LCS model, strip out the evolutionary mechanism, simplify the reinforcement learning procedure and equip the agent with the ability of associative perception, adopted from psychology. To improve our understanding of the nature and structure of maze environments, we analyze mazes used in research for the last two decades, introduce a set of maze complexity characteristics, and develop a set of new maze environments. We then run our new LCS with associative perception through the old and new aliasing mazes, which represent partially observable Markov decision problems (POMDP) and demonstrate that it performs at least as well as, and in some cases better than, other published systems

    Improved Outcomes in Auditory Brainstem Implantation with the Use of Near-Field Electrical Compound Action Potentials.

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    Among the 202 patients with auditory brainstem implants fitted and monitored with electrical auditory brainstem response during implant fitting, 9 also underwent electrical compound action potential recording. These subjects were matched retrospectively with a control group of 9 patients in whom only the electrical auditory brainstem response was recorded. Electrical compound action potentials were obtained using a cotton-wick recording electrode located near the surface of the cochlear nuclei and on several cranial nerves. Significantly lower potential thresholds were observed with the recording electrode located on the cochlear nuclei surface compared with the electrical auditory brainstem response (104.4 ± 32.5 vs 158.9 ± 24.2, P = .0030). Electrical brainstem response and compound action potentials identified effects on the neighboring cranial nerves on 3.2 ± 2.4 and 7.8 ± 3.2 electrodes, respectively (P = .0034). Open-set speech perception outcomes at 48-month follow-up had improved significantly in the near- versus far-field recording groups (78.9% versus 56.7%; P = .0051). Electrical compound action potentials during auditory brainstem implantation significantly improved the definition of the potential threshold and the number of auditory and extra-auditory waves generated. It led to the best coupling between the electrode array and cochlear nuclei, significantly improving the overall open-set speech perception

    Exploring causes of interannual variability in the seasonal cycles of tropospheric nitrous oxide

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    Seasonal cycles in the mixing ratios of tropospheric nitrous oxide (N[subscript 2]O) are derived by detrending long-term measurements made at sites across four global surface monitoring networks. The detrended monthly data display large interannual variability, which at some sites challenges the concept of a "mean" seasonal cycle. In the Northern Hemisphere, correlations between polar winter lower stratospheric temperature and detrended N[subscript 2]O data, around the month of the seasonal minimum, provide empirical evidence for a stratospheric influence, which varies in strength from year to year and can explain much of the interannual variability in the surface seasonal cycle. Even at sites where a strong, competing, regional N[subscript 2]O source exists, such as from coastal upwelling at Trinidad Head, California, the stratospheric influence must be understood to interpret the biogeochemical signal in monthly mean data. In the Southern Hemisphere, detrended surface N[subscript 2]O monthly means are correlated with polar spring lower stratospheric temperature in months preceding the N[subscript 2]O minimum, providing empirical evidence for a coherent stratospheric influence in that hemisphere as well, in contrast to some recent atmospheric chemical transport model (ACTM) results. Correlations between the phasing of the surface N[subscript 2]O seasonal cycle in both hemispheres and both polar lower stratospheric temperature and polar vortex break-up date provide additional support for a stratospheric influence. The correlations discussed above are generally more evident in high-frequency in situ data than in data from weekly flask samples. Furthermore, the interannual variability in the N[subscript 2]O seasonal cycle is not always correlated among in situ and flask networks that share common sites, nor do the mean seasonal amplitudes always agree. The importance of abiotic influences such as the stratospheric influx and tropospheric transport on N[subscript 2]O seasonal cycles suggests that, at sites remote from local sources, surface N[subscript 2]O mixing ratio data by themselves are unlikely to provide information about seasonality in surface sources, e.g., for atmospheric inversions, unless the ACTMs employed in the inversions accurately account for these influences. An additional abioitc influence is the seasonal ingassing and outgassing of cooling and warming surface waters, which creates a thermal signal in tropospheric N[subscript 2]O that is of particular importance in the extratropical Southern Hemisphere, where it competes with the biological ocean source signal.United States. National Aeronautics and Space Administration (grant NNX08AB48G

    In situ measurements of atmospheric O2 and CO2 reveal an unexpected O2 signal over the tropical Atlantic Ocean

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    We present the first meridional transects of atmospheric O2 and CO2 over the Atlantic Ocean. We combine these measurements into the tracer atmospheric potential oxygen (APO), which is a measure of the oceanic contribution to atmospheric O2 variations. Our new in situ measurement system, deployed on board a commercial container ship during 2015, performs as well as or better than existing similar measurement systems. The data show small short-term variability (hours to days), a step-change corresponding to the position of the Intertropical Convergence Zone (ITCZ), and seasonal cycles that vary with latitude. In contrast to data from the Pacific Ocean and to previous modeling studies, our Atlantic Ocean APO data show no significant bulge in the tropics. This difference cannot be accounted for by interannual variability in the position of the ITCZ or the Atlantic Meridional Mode Index and appears to be a persistent feature of the Atlantic Ocean system. Modeled APO using the TM3 atmospheric transport model does exhibit a significant bulge over the Atlantic and overestimates the interhemispheric gradient in APO over the Atlantic Ocean. These results indicate that either there are inaccuracies in the oceanic flux data products in the equatorial Atlantic Ocean region, or that there are atmospheric transport inaccuracies in the model, or a combination of both. Our shipboard O2 and CO2 measurements are ongoing and will reveal the long-term nature of equatorial APO outgassing over the Atlantic as more data become available

    Co-Housing Rodents with Different Coat Colours as a Simple, Non-Invasive Means of Individual Identification:Validating Mixed-Strain Housing for C57BL/6 and DBA/2 Mice

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    Standard practice typically requires the marking of laboratory mice so that they can be individually identified. However, many of the common methods compromise the welfare of the individuals being marked (as well as requiring time, effort, and/or resources on the part of researchers and technicians). Mixing strains of different colour within a cage would allow them to be readily visually identifiable, negating the need for more invasive marking techniques. Here we assess the impact that mixed strain housing has on the phenotypes of female C57BL/6 (black) and DBA/2 (brown) mice, and on the variability in the data obtained from them. Mice were housed in either mixed strain or single strain pairs for 19 weeks, and their phenotypes then assessed using 23 different behavioural, morphological, haematological and physiological measures widely used in research and/or important for assessing mouse welfare. No negative effects of mixed strain housing could be found on the phenotypes of either strain, including variables relevant to welfare. Differences and similarities between the two strains were almost all as expected from previously published studies, and none were affected by whether mice were housed in mixed- or single-strain pairs. Only one significant main effect of housing type was detected: mixed strain pairs had smaller red blood cell distribution widths, a measure suggesting better health (findings that now need replicating in case they were Type 1 errors resulting from our multiplicity of tests). Furthermore, mixed strain housing did not increase the variation in data obtained from the mice: the standard errors for all variables were essentially identical between the two housing conditions. Mixed strain housing also made animals very easy to distinguish while in the home cage. Female DBA/2 and C57BL/6 mice can thus be housed in mixed strain pairs for identification purposes, with no apparent negative effects on their welfare or the data they generate. This suggests that there is much value in exploring other combinations of strains
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