The Experts below are selected from a list of 42165 Experts worldwide ranked by ideXlab platform
Conor K Gately - One of the best experts on this subject based on the ideXlab platform.
-
assessing urban methane emissions using column observing portable fourier transform infrared ftir spectrometers and a novel bayesian inversion framework
Atmospheric Chemistry and Physics, 2021Co-Authors: Taylor Jones, Jonathan Franklin, Jia Chen, Florian Dietrich, Kristian D Hajny, Johannes C Paetzold, Adrian Wenzel, Conor K GatelyAbstract:Abstract. Cities represent a large and concentrated portion of global greenhouse gas emissions, including methane. Quantifying methane emissions from urban areas is difficult, and inventories made using bottom-up accounting methods often differ greatly from top-down estimates generated from atmospheric observations. Emissions from leaks in natural gas infrastructure are difficult to predict and are therefore poorly constrained in bottom-up inventories. Natural gas infrastructure leaks and emissions from end uses can be spread throughout the city, and this Diffuse Source can represent a significant fraction of a city's total emissions. We investigated Diffuse methane emissions of the city of Indianapolis, USA, during a field campaign in May 2016. A network of five portable solar-tracking Fourier transform infrared (FTIR) spectrometers was deployed throughout the city. These instruments measure the mole fraction of methane in a total column of air, giving them sensitivity to larger areas of the city than in situ sensors at the surface. We present an innovative inversion method to link these total column concentrations to surface fluxes. This method combines a Lagrangian transport model with a Bayesian inversion framework to estimate surface emissions and their uncertainties, together with determining the concentrations of methane in the air flowing into the city. Variations exceeding 10 ppb were observed in the inflowing air on a typical day, which is somewhat larger than the enhancements due to urban emissions ( ppb downwind of the city). We found Diffuse methane emissions of 73(±22 ) mol s−1 , which is about 50 % of the urban total and 68 % higher than estimated from bottom-up methods, although it is somewhat smaller than estimates from studies using tower and aircraft observations. The measurement and model techniques developed here address many of the challenges present when quantifying urban greenhouse gas emissions and will help in the design of future measurement schemes in other cities.
-
assessing urban methane emissions using column observingportable ftir spectrometers and a novel bayesian inversionframework
Atmospheric Chemistry and Physics, 2021Co-Authors: Taylor Jones, Jonathan Franklin, Jia Chen, Florian Dietrich, Kristian D Hajny, Johannes C Paetzold, Adrian Wenzel, Conor K GatelyAbstract:Abstract. Cities represent a large and concentrated portion of global greenhouse gas emissions, including methane. Quantifying methane emissions from urban areas is difficult, and inventories made using bottom-up accounting methods often differ greatly from top-down estimates generated from atmospheric observations. Emissions from leaks in natural gas infrastructure are difficult to predict, and are therefore poorly constrained in bottom-up inventories. Natural gas infrastructure leaks and emissions from end uses can be spread throughout the city, and this Diffuse Source can represent a significant fraction of a city's total emissions. We investigated Diffuse methane emissions of the city of Indianapolis, USA during a field campaign in May of 2016. A network of five portable solar-tracking Fourier transform infrared (FTIR) spectrometers was deployed throughout the city. These instruments measure the mole fraction of methane in a total column of air, giving them sensitivity to larger areas of the city than in situ sensors at the surface. We present an innovative inversion method to link these total column concentrations to surface fluxes. This method combines a Lagrangian transport model with a Bayesian inversion framework to estimate surface emissions and their uncertainties, together with determining the concentrations of methane in the air flowing into the city. Variations exceeding 10 ppb were observed in the inflowing air on a typical day, somewhat larger than the enhancements due to urban emissions (
Me Nord - One of the best experts on this subject based on the ideXlab platform.
-
evidence of a weak galactic center magnetic field from Diffuse low frequency nonthermal radio emission
The Astrophysical Journal, 2005Co-Authors: Tn Larosa, Cl Brogan, Steven N Shore, Tj Lazio, Ne Kassim, Me NordAbstract:New low-frequency 74 and 330 MHz observations of the Galactic center (GC) region reveal the presence of a large-scale (6° × 2°) Diffuse Source of nonthermal synchrotron emission. A minimum-energy analysis of this emission yields a total energy of ~(4/7f3/7) × 1052 ergs and a magnetic field strength of ~6(/f)2/7 μG (where is the proton to electron energy ratio and f is the filling factor of the synchrotron emitting gas). The equipartition particle energy density is 1.2(/f)2/7 eV cm-3, a value consistent with cosmic-ray data. However, the derived magnetic field is several orders of magnitude below the 1 mG field commonly invoked for the GC. With this field the Source can be maintained with the supernova rate inferred from the GC star formation. Furthermore, a strong magnetic field implies an abnormally low GC cosmic-ray energy density. We conclude that the mean magnetic field in the GC region must be weak, of order 10 μG (at least on size scales 125'').
Taylor Jones - One of the best experts on this subject based on the ideXlab platform.
-
assessing urban methane emissions using column observing portable fourier transform infrared ftir spectrometers and a novel bayesian inversion framework
Atmospheric Chemistry and Physics, 2021Co-Authors: Taylor Jones, Jonathan Franklin, Jia Chen, Florian Dietrich, Kristian D Hajny, Johannes C Paetzold, Adrian Wenzel, Conor K GatelyAbstract:Abstract. Cities represent a large and concentrated portion of global greenhouse gas emissions, including methane. Quantifying methane emissions from urban areas is difficult, and inventories made using bottom-up accounting methods often differ greatly from top-down estimates generated from atmospheric observations. Emissions from leaks in natural gas infrastructure are difficult to predict and are therefore poorly constrained in bottom-up inventories. Natural gas infrastructure leaks and emissions from end uses can be spread throughout the city, and this Diffuse Source can represent a significant fraction of a city's total emissions. We investigated Diffuse methane emissions of the city of Indianapolis, USA, during a field campaign in May 2016. A network of five portable solar-tracking Fourier transform infrared (FTIR) spectrometers was deployed throughout the city. These instruments measure the mole fraction of methane in a total column of air, giving them sensitivity to larger areas of the city than in situ sensors at the surface. We present an innovative inversion method to link these total column concentrations to surface fluxes. This method combines a Lagrangian transport model with a Bayesian inversion framework to estimate surface emissions and their uncertainties, together with determining the concentrations of methane in the air flowing into the city. Variations exceeding 10 ppb were observed in the inflowing air on a typical day, which is somewhat larger than the enhancements due to urban emissions ( ppb downwind of the city). We found Diffuse methane emissions of 73(±22 ) mol s−1 , which is about 50 % of the urban total and 68 % higher than estimated from bottom-up methods, although it is somewhat smaller than estimates from studies using tower and aircraft observations. The measurement and model techniques developed here address many of the challenges present when quantifying urban greenhouse gas emissions and will help in the design of future measurement schemes in other cities.
-
assessing urban methane emissions using column observingportable ftir spectrometers and a novel bayesian inversionframework
Atmospheric Chemistry and Physics, 2021Co-Authors: Taylor Jones, Jonathan Franklin, Jia Chen, Florian Dietrich, Kristian D Hajny, Johannes C Paetzold, Adrian Wenzel, Conor K GatelyAbstract:Abstract. Cities represent a large and concentrated portion of global greenhouse gas emissions, including methane. Quantifying methane emissions from urban areas is difficult, and inventories made using bottom-up accounting methods often differ greatly from top-down estimates generated from atmospheric observations. Emissions from leaks in natural gas infrastructure are difficult to predict, and are therefore poorly constrained in bottom-up inventories. Natural gas infrastructure leaks and emissions from end uses can be spread throughout the city, and this Diffuse Source can represent a significant fraction of a city's total emissions. We investigated Diffuse methane emissions of the city of Indianapolis, USA during a field campaign in May of 2016. A network of five portable solar-tracking Fourier transform infrared (FTIR) spectrometers was deployed throughout the city. These instruments measure the mole fraction of methane in a total column of air, giving them sensitivity to larger areas of the city than in situ sensors at the surface. We present an innovative inversion method to link these total column concentrations to surface fluxes. This method combines a Lagrangian transport model with a Bayesian inversion framework to estimate surface emissions and their uncertainties, together with determining the concentrations of methane in the air flowing into the city. Variations exceeding 10 ppb were observed in the inflowing air on a typical day, somewhat larger than the enhancements due to urban emissions (
Bradley E Schaefer - One of the best experts on this subject based on the ideXlab platform.
-
the Diffuse Source at the center of lmc snr 0509 67 5 is a background galaxy at z 0 031
The Astrophysical Journal, 2014Co-Authors: Ashley Pagnotta, Emma S Walker, Bradley E SchaeferAbstract:Type Ia supernovae (SNe Ia) are well-known for their use in the measurement of cosmological distances, but our continuing lack of concrete knowledge about their progenitor stars is both a matter of debate and a Source of systematic error. In our attempts to answer this question, we presented unambiguous evidence that LMC SNR 0509−67.5, the remnant of an SN Ia that exploded in the Large Magellanic Cloud 400 ± 50 yr ago, did not have any point Sources (stars) near the site of the original supernova explosion, from which we concluded that this particular supernova must have had a progenitor system consisting of two white dwarfs. There is, however, evidence of nebulosity near the center of the remnant, which could have been left over detritus from the less massive WD, or could have been a background galaxy unrelated to the supernova explosion. We obtained long-slit spectra of the central nebulous region using GMOS on Gemini South to determine which of these two possibilities is correct. The spectra show Hα emission at a redshift of z = 0.031, which implies that the nebulosity in the center of LMC SNR 0509−67.5 is a background galaxy, unrelated to the supernova.
-
the Diffuse Source at the center of lmc snr 0509 67 5 is a background galaxy at z 0 031
arXiv: Solar and Stellar Astrophysics, 2014Co-Authors: Ashley Pagnotta, Emma S Walker, Bradley E SchaeferAbstract:Type Ia supernovae (SNe Ia) are well-known for their use in the measurement of cosmological distances, but our continuing lack of concrete knowledge about their progenitor stars is both a matter of debate and a Source of systematic error. In our attempts to answer this question, we presented unambiguous evidence that LMC SNR 0509-67.5, the remnant of an SN Ia that exploded in the Large Magellanic Cloud 400 +/- 50 years ago, did not have any point Sources (stars) near the site of the original supernova explosion, from which we concluded that this particular supernova must have had a progenitor system consisting of two white dwarfs (Schaefer & Pagnotta 2012). There is, however, evidence of nebulosity near the center of the remnant, which could have been left over detritus from the less massive WD, or could have been a background galaxy unrelated to the supernova explosion. We obtained long-slit spectra of the central nebulous region using GMOS on Gemini South to determine which of these two possibilities is correct. The spectra show H-alpha emission at a redshift of z = 0.031, which implies that the nebulosity in the center of LMC SNR 0509-67.5 is a background galaxy, unrelated to the supernova.
Dingjiang Chen - One of the best experts on this subject based on the ideXlab platform.
-
a modified load apportionment model for identifying point and Diffuse Source nutrient inputs to rivers from stream monitoring data
Journal of Hydrology, 2013Co-Authors: Dingjiang Chen, Randy A DahlgrenAbstract:Summary Determining point (PS) and Diffuse Source (DS) nutrient inputs to rivers is essential for assessing and developing mitigation strategies to reduce excessive nutrient loads that induce eutrophication. However, application of watershed mechanistic models to assess nutrient inputs is limited by large data requirements and intensive model calibration efforts. Simple export coefficient models and statistical models also require extensive primary watershed attribute information and further they cannot address seasonal patterns of nutrient delivery. In practice, monitoring efforts to identify all PSs within a watershed are very difficult due to time and economic limitations. To overcome these issues, based on the fundamental hydrological differences between PS and DS pollution, a modified load apportionment model (LAM) was developed relating the river nutrient load to nutrient inputs from PS, DS and upstream inflow Sources while adjusting for in-stream nutrient retention processes. Estimates of PS and DS inputs can be easily achieved through Bayesian calibration of the five model parameters from commonly available stream monitoring data. It considers in-stream nutrient retention processes, temporal changes of PS and DS inputs, and nutrient contributions from upstream inflow waters, as well as the uncertainty associated with load estimations. The efficacy of this modified LAM was demonstrated for total nitrogen (TN) Source apportionment using a 6-year record of monthly water quality data for the ChangLe River in eastern China. Aimed at attaining the targeted river TN concentration (2 mg L−1), required input load reductions for PS, DS and upstream inflow were estimated. This modified LAM is applicable for both district-based and catchment-based water quality management strategies with limited data requirements, providing a simple, effective and economical tool for apportioning PS and DS nutrient inputs to rivers.
-
a modified load apportionment model for identifying point and Diffuse Source nutrient inputs to rivers from stream monitoring data
Journal of Hydrology, 2013Co-Authors: Dingjiang Chen, Randy A DahlgrenAbstract:Determining point (PS) and Diffuse Source (DS) nutrient inputs to rivers is essential for assessing and developing mitigation strategies to reduce excessive nutrient loads that induce eutrophication. However, application of watershed mechanistic models to assess nutrient inputs is limited by large data requirements and intensive model calibration efforts. Simple export coefficient models and statistical models also require extensive primary watershed attribute information and further they cannot address seasonal patterns of nutrient delivery. In practice, monitoring efforts to identify all PSs within a watershed are very difficult due to time and economic limitations. To overcome these issues, based on the fundamental hydrological differences between PS and DS pollution, a modified load apportionment model (LAM) was developed relating the river nutrient load to nutrient inputs from PS, DS and upstream inflow Sources while adjusting for in-stream nutrient retention processes. Estimates of PS and DS inputs can be easily achieved through Bayesian calibration of the five model parameters from commonly available stream monitoring data. It considers in-stream nutrient retention processes, temporal changes of PS and DS inputs, and nutrient contributions from upstream inflow waters, as well as the uncertainty associated with load estimations. The efficacy of this modified LAM was demonstrated for total nitrogen (TN) Source apportionment using a 6-year record of monthly water quality data for the ChangLe River in eastern China. Aimed at attaining the targeted river TN concentration (2mgL-1), required input load reductions for PS, DS and upstream inflow were estimated. This modified LAM is applicable for both district-based and catchment-based water quality management strategies with limited data requirements, providing a simple, effective and economical tool for apportioning PS and DS nutrient inputs to rivers. © 2013 Elsevier B.V.
-
estimation of critical nutrient amounts based on input output analysis in an agriculture watershed of eastern china
Agriculture Ecosystems & Environment, 2009Co-Authors: Dingjiang Chen, Randy A Dahlgren, Yena Shen, Shuquan JinAbstract:Abstract The concept of critical nutrient amounts (CNA) for a watershed was developed to address eutrophication in surface waters from Diffuse (non-point) Source pollution. CNA is defined as the maximum allowable applied or generated amount (AGA) of a nutrient from natural and human Sources that can be emitted and still allow compliance with water quality standards. The CNA calculation method is based on properties of Diffuse Source pollution, including (i) estimation and analysis of nutrient input–output balances in terrestrial and riverine systems; (ii) prediction of terrestrial nutrient export loads and AGA using riverine loads; and (iii) calculation of critical AGA to meet different regulatory compliance locations (e.g., end of a reach or for the whole reach). The CNA concept was developed, validated and applied for total nitrogen (TN) and phosphorus (TP) in the ChangLe agriculture-dominated watershed (864 km 2 /27.8 km reach) of eastern China. Results indicated that CNA was 7174 t N y −1 and 5004 t P y −1 for the reach-end control method and 8290 t N y −1 and 4425 t P y −1 for the whole-reach control method. Annual TN AGA exceeded CNA by 53.2–61.3% and 46.0–55.2% for reach-end and whole-reach control methods in 2004–06, respectively. In contrast, TP AGA values were 90.3–95.9% and 68.3–73.2% below CNA values for reach-end and whole-reach control methods, respectively. These calculations provide a target or permissible nutrient amount that can be used to develop management practices that allow attainment of water quality objectives at the watershed scale.