scholarly journals Atmospheric measurement of point source fossil fuel CO<sub>2</sub> emissions

2013 ◽  
Vol 13 (11) ◽  
pp. 29059-29095
Author(s):  
J. C. Turnbull ◽  
E. D. Keller ◽  
W. T. Baisden ◽  
G. Brailsford ◽  
T. Bromley ◽  
...  
Keyword(s):  
Point Source ◽  
Fossil Fuel ◽  
Dispersion Model ◽  
Treatment Plant ◽  
Plume Dispersion ◽  
Atmospheric Measurements ◽  
Gas Treatment ◽  
Atmospheric Observations ◽  
Meteorological Observations

Abstract. We use the Kapuni Gas Treatment Plant to examine methodologies for atmospheric monitoring of point source fossil fuel CO2 (CO2ff) emissions. The Kapuni plant, located in rural New Zealand, removes CO2 from locally extracted natural gas and vents that CO2 to the atmosphere, at a rate of ~0.1 Tg carbon per year. The plant is located in a rural dairy farming area, with no other significant CO2ff sources nearby, but large, diurnally varying, biospheric CO2 fluxes from the surrounding highly productive agricultural grassland. We made flask measurements of CO2 and 14CO2 (from which we derive the CO2ff component) and in situ measurements of CO2 downwind of the Kapuni plant, using a Helikite to sample transects across the emission plume from the surface up to 100 m a.g.l. We also determined the surface CO2ff content averaged over several weeks from the 14CO2 content of grass samples collected from the surrounding area. We use the WindTrax plume dispersion model to compare the atmospheric observations with the emissions reported by the Kapuni plant, and to determine how well atmospheric measurements can constrain the emissions. The model has difficulty accurately capturing the fluctuations and short-term variability in the Helikite samples, but does quite well in representing the observed CO2ff in 15 min averaged surface flask samples and in ~1 week integrated CO2ff averages from grass samples. In this pilot study, we found that using grass samples, the modeled and observed CO2ff emissions averaged over one week agreed to within 30%. The results imply that greater verification accuracy may be achieved by including more detailed meteorological observations and refining 14CO2 sampling strategies.

scholarly journals Atmospheric measurement of point source fossil CO<sub>2</sub> emissions

2014 ◽  
Vol 14 (10) ◽  
pp. 5001-5014 ◽  
Author(s):  
J. C. Turnbull ◽  
E. D. Keller ◽  
T. Baisden ◽  
G. Brailsford ◽  
T. Bromley ◽  
...  
Keyword(s):  
Point Source ◽  
Dispersion Model ◽  
Treatment Plant ◽  
Ground Level ◽  
Plume Dispersion ◽  
Atmospheric Measurements ◽  
Gas Treatment ◽  
Atmospheric Observations ◽  
Meteorological Observations

Abstract. We use the Kapuni Gas Treatment Plant to examine methodologies for atmospheric monitoring of point source fossil fuel CO2 (CO2ff) emissions. The Kapuni plant, located in rural New Zealand, removes CO2 from locally extracted natural gas and vents that CO2 to the atmosphere, at a rate of ~0.1 Tg carbon per year. The plant is located in a rural dairy farming area, with no other significant CO2ff sources nearby, but large, diurnally varying, biospheric CO2 fluxes from the surrounding highly productive agricultural grassland. We made flask measurements of CO2 and 14CO2 (from which we derive the CO2ff component) and in situ measurements of CO2 downwind of the Kapuni plant, using a Helikite to sample transects across the emission plume from the surface up to 100 m above ground level. We also determined the surface CO2ff content averaged over several weeks from the 14C content of grass samples collected from the surrounding area. We use the WindTrax plume dispersion model to compare the atmospheric observations with the emissions reported by the Kapuni plant, and to determine how well atmospheric measurements can constrain the emissions. The model has difficulty accurately capturing the fluctuations and short-term variability in the Helikite samples, but does quite well in representing the observed CO2ff in 15 min averaged surface flask samples and in ~ one week integrated CO2ff averages from grass samples. In this pilot study, we found that using grass samples, the modeled and observed CO2ff emissions averaged over one week agreed to within 30%. The results imply that greater verification accuracy may be achieved by including more detailed meteorological observations and refining 14C sampling strategies.

scholarly journals Estimating US fossil fuel CO2emissions from measurements of14C in atmospheric CO2

2020 ◽  
Vol 117 (24) ◽  
pp. 13300-13307 ◽  
Author(s):  
Sourish Basu ◽  
Scott J. Lehman ◽  
John B. Miller ◽  
Arlyn E. Andrews ◽  
Colm Sweeney ◽  
...  
Keyword(s):  
Environmental Protection Agency ◽  
Fossil Fuel ◽  
Net Ecosystem Exchange ◽  
The United States ◽  
Reference Network ◽  
Random Errors ◽  
Atmospheric Measurements ◽  
Modeling Framework ◽  
Emission Data ◽  
Atmospheric Observations

We report national scale estimates of CO2emissions from fossil-fuel combustion and cement production in the United States based directly on atmospheric observations, using a dual-tracer inverse modeling framework and CO2andΔ14CO2measurements obtained primarily from the North American portion of the National Oceanic and Atmospheric Administration’s Global Greenhouse Gas Reference Network. The derived US national total for 2010 is 1,653 ± 30 TgC yr−1with an uncertainty (1σ) that takes into account random errors associated with atmospheric transport, atmospheric measurements, and specified prior CO2and14C fluxes. The atmosphere-derived estimate is significantly larger (>3σ) than US national emissions for 2010 from three global inventories widely used for CO2accounting, even after adjustments for emissions that might be sensed by the atmospheric network, but which are not included in inventory totals. It is also larger (>2σ) than a similarly adjusted total from the US Environmental Protection Agency (EPA), but overlaps EPA’s reported upper 95% confidence limit. In contrast, the atmosphere-derived estimate is within1σof the adjusted 2010 annual total and nine of 12 adjusted monthly totals aggregated from the latest version of the high-resolution, US-specific “Vulcan” emission data product. Derived emissions appear to be robust to a range of assumed prior emissions and other parameters of the inversion framework. While we cannot rule out a possible bias from assumed prior Net Ecosystem Exchange over North America, we show that this can be overcome with additionalΔ14CO2measurements. These results indicate the strong potential for quantification of US emissions and their multiyear trends from atmospheric observations.

scholarly journals Methane emissions from the Munich Oktoberfest

2020 ◽  
Vol 20 (6) ◽  
pp. 3683-3696 ◽  
Author(s):  
Jia Chen ◽  
Florian Dietrich ◽  
Hossein Maazallahi ◽  
Andreas Forstmaier ◽  
Dominik Winkler ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Plume Dispersion ◽  
Emission Inventories ◽  
Ch4 Emissions ◽  
Policies And Measures ◽  
Future Emission ◽  
Gaussian Plume ◽  
Reduce Emissions ◽  
Limited Duration

Abstract. This study presents the first investigation of the methane (CH4) emissions of a large festival. Munich Oktoberfest, the world's largest folk festival, is a potential source of CH4 as a large amount of natural gas for cooking and heating is used. In 2018 we measured the CH4 emissions of Oktoberfest using in situ measurements combined with a Gaussian plume dispersion model. Measurements were taken while walking and biking around the perimeter of the Oktoberfest premises (Theresienwiese) at different times of the day, during the week and at the weekend. The measurements showed enhancements of up to 100 ppb compared to background values and measurements after Oktoberfest. The average emission flux of Oktoberfest is determined as (6.7±0.6) µg (m2 s)−1. Additional analyses, including the daily emission cycle and comparisons between emissions and the number of visitors, suggest that CH4 emissions of Oktoberfest are not due solely to the human biogenic emissions. Instead, fossil fuel CH4 emissions, such as incomplete combustion or loss in the gas appliances, appear to be the major contributors to Oktoberfest emissions. Our results can help to develop CH4 reduction policies and measures to reduce emissions at festivals and other major events in cities. Furthermore, events with a limited duration have not yet been included in the state-of-the-art emission inventories, such as TNO-MACC, EDGAR or IER. Our investigations show that these emissions are not negligible. Therefore, these events should be included in future emission inventories.

scholarly journals Mobile atmospheric measurements and local-scale inverse estimation of the location and rates of brief CH<sub>4</sub> and CO<sub>2</sub> releases from point sources

2021 ◽  
Vol 14 (9) ◽  
pp. 5987-6003
Author(s):  
Pramod Kumar ◽  
Grégoire Broquet ◽  
Camille Yver-Kwok ◽  
Olivier Laurent ◽  
Susan Gichuki ◽  
...  
Keyword(s):  
Mole Fraction ◽  
Cross Sections ◽  
Dispersion Model ◽  
Local Scale ◽  
Point Sources ◽  
Mitigation Strategies ◽  
Dispersion Modeling ◽  
Plume Dispersion ◽  
Atmospheric Measurements ◽  
Wide Range

Abstract. We present a local-scale atmospheric inversion framework to estimate the location and rate of methane (CH4) and carbon dioxide (CO2) releases from point sources. It relies on mobile near-ground atmospheric CH4 and CO2 mole fraction measurements across the corresponding atmospheric plumes downwind of these sources, on high-frequency meteorological measurements, and on a Gaussian plume dispersion model. The framework exploits the scatter of the positions of the individual plume cross sections, the integrals of the gas mole fractions above the background within these plume cross sections, and the variations of these integrals from one cross section to the other to infer the position and rate of the releases. It has been developed and applied to provide estimates of brief controlled CH4 and CO2 point source releases during a 1-week campaign in October 2018 at the TOTAL experimental platform TADI in Lacq, France. These releases typically lasted 4 to 8 min and covered a wide range of rates (0.3 to 200 g CH4/s and 0.2 to 150 g CO2/s) to test the capability of atmospheric monitoring systems to react fast to emergency situations in industrial facilities. It also allowed testing of their capability to provide precise emission estimates for the application of climate change mitigation strategies. However, the low and highly varying wind conditions during the releases added difficulties to the challenge of characterizing the atmospheric transport over the very short duration of the releases. We present our series of CH4 and CO2 mole fraction measurements using instruments on board a car that drove along roads ∼50 to 150 m downwind of the 40 m × 60 m area for controlled releases along with the estimates of the release locations and rates. The comparisons of these results to the actual position and rate of the controlled releases indicate ∼10 %–40 % average errors (depending on the inversion configuration or on the series of tests) in the estimates of the release rates and ∼30–40 m errors in the estimates of the release locations. These results are shown to be promising, especially since better results could be expected for longer releases and under meteorological conditions more favorable to local-scale dispersion modeling. However, the analysis also highlights the need for methodological improvements to increase the skill for estimating the source locations.

scholarly journals Mobile atmospheric measurements and local-scale inverse estimation of the location and rates of brief CH<sub>4</sub> and CO<sub>2</sub> releases from point sources

2020 ◽  
Author(s):  
Pramod Kumar ◽  
Grégoire Broquet ◽  
Camille Yver-Kwok ◽  
Olivier Laurent ◽  
Susan Gichuki ◽  
...  
Keyword(s):  
Cross Sections ◽  
Dispersion Model ◽  
Local Scale ◽  
Point Sources ◽  
Mitigation Strategies ◽  
Average Error ◽  
Dispersion Modeling ◽  
Plume Dispersion ◽  
Atmospheric Measurements ◽  
Wide Range

Abstract. We present a local-scale atmospheric inversion framework to estimate the location and rate of methane (CH4) and carbon dioxide (CO2) releases from point sources. It relies on mobile near-ground atmospheric CH4 and CO2 mole fraction measurements across the corresponding atmospheric plumes downwind the sources, on high-frequency meteorological measurements, and a Gaussian plume dispersion model. It exploits the spread of the positions of individual plume cross-sections and the integrals of the gas mole fractions above the background within these plume cross-sections to infer the position and rate of the releases. It has been developed and applied to provide estimates of brief controlled CH4 and CO2 point source releases during a one-week campaign in October 2018 at the TOTAL's experimental platform TADI in Lacq, France. These releases lasted typically 4 to 8 minutes and covered a wide range of rates (0.3 to 200 gCH4/s and 0.2 to 150 gCO2/s) to test the capability of atmospheric monitoring systems to react fast to emergency situations in industrial facilities. It also allowed testing their capability to provide precise emission estimates for the application of climate change mitigation strategies. However, the low and highly varying wind conditions during the releases added difficulties to the challenge of characterizing the atmospheric transport over the very short duration of the releases. We present our series of measurements of CH4 and CO2 mole fractions using instruments onboard a car that drives along the roads ~50 to 150 m downwind the 40 m × 60 m area of controlled releases for each of the releases and the results from the inversions of the release locations and rates. The comparisons of these results to the actual position and rate of the controlled release indicate a 20 %–30 % average error on the release rates and a ~30–40 m errors in the estimates of the release locations. These results are shown to be promising especially since better results could be expected for longer releases and under meteorological conditions more favorable to local scale dispersion modeling.

Multiscale Natural Gas Emissions Observations of the San Juan, NM Coal Mine: Inversion Using Plume and Neural Network Models

2021 ◽  
Author(s):  
Aaron Meyer ◽  
Rodica Lindenmaier ◽  
Bryan Travis ◽  
Sajjan Heerah ◽  
Manvendra Dubey
Keyword(s):  
Neural Network ◽  
Natural Gas ◽  
Coal Mine ◽  
Detection System ◽  
Dispersion Model ◽  
San Juan ◽  
Plume Dispersion ◽  
Source Inversion ◽  
Neural Network Models

&lt;p&gt;Methane (CH&lt;sub&gt;4&lt;/sub&gt;) is a potent greenhouse gas; therefore, accurate measurement of its sources is important for climate research. Because of the diversity of methane sources, identifying and apportioning different sources is essential.&amp;#160; We demonstrate our ability characterize a specific source using top-down atmospheric observations downwind of a coal mine vent shaft, a large natural gas source, in San Juan, NM. To facilitate a field campaign in December of 2020, a mobile platform was developed to make simultaneous in situ observations of methane and ethane (C&lt;sub&gt;2&lt;/sub&gt;H&lt;sub&gt;6&lt;/sub&gt;) with an Aeris mid-IR spectrometer and wind velocities with a Trisonica mini 3-D anemometer. Total column methane was also measured during the campaign using an EM27/SUN mobile solar Fourier transform spectrometer (FTS) and compared with column methane and ethane measured in March of 2013 using higher resolution FTS instruments at a TCCON station near the site&lt;sup&gt;1&lt;/sup&gt;. Our in situ data shows a unique and stable C&lt;sub&gt;2&lt;/sub&gt;H&lt;sub&gt;6&lt;/sub&gt;:CH&lt;sub&gt;4 &lt;/sub&gt;ratio of 1-2% in the vent plume that agrees well with the 1.5% ratio measured by the TCCON FTS instruments in 2013, demonstrating that consistent attribution can be made using both in situ and remote methods. Furthermore, we infer the mass flux of methane and ethane from the vent shaft using a simple plume dispersion model and multiple measurements around the vent shaft. This direct source inversion is compared to results from a trained neural network code we have developed for source location and quantification (ALFaLDS)&lt;sup&gt;2&lt;/sup&gt;. Our results demonstrate how multiscale measurements, inverse modeling, and machine learning can be used to better attribute and constrain methane emissions.&lt;/p&gt;&lt;p&gt;&lt;sup&gt;1 &lt;/sup&gt;Lindenmaier, R.&amp;#160; et al.: Multiscale observations of CO&lt;sub&gt;2&lt;/sub&gt;, &lt;sup&gt;13&lt;/sup&gt;CO&lt;sub&gt;2&lt;/sub&gt;, and pollutants at Four Corners for emission verification and attribution, Proc. Natl. Acad. Sci., 111 (23), 8386-8391, https://doi.org/10.1073/pnas.1321883111, 2014.&lt;/p&gt;&lt;p&gt;&lt;sup&gt;2 &lt;/sup&gt;Travis, B., Dubey, M. and Sauer J.: Neural networks to locate and quantify fugitive natural gas leaks for a MIR detection system, Atmos. Environ: X, 8, (2020) 100092, https://doi.org/10.1016/j.aeaoa.2020.100092, 2020.&lt;/p&gt;

Assessments of in situ and remotely sensed CO2 observations in a Carbon Cycle Fossil Fuel Data Assimilation System to estimate fossil fuel emissions

2020 ◽  
Author(s):  
Marko Scholze ◽  
Thomas Kaminski ◽  
Peter Rayner ◽  
Michael Vossbeck ◽  
Michael Buchwitz ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Fossil Fuel ◽  
Greenhouse Gas Emission ◽  
Atmospheric Measurements ◽  
Mode Of Operation ◽  
Emission Estimate ◽  
Annual Scale ◽  
Assimilation System ◽  
Fossil Fuel Emissions

&lt;p&gt;The Paris Agreement establishes a transparency framework that builds upon&amp;#160;inventory-based national greenhouse gas emission reports, complemented by independent emission&amp;#160;estimates derived from atmospheric measurements through inverse modelling.&amp;#160;The capability of such a Monitoring and Verification Support (MVS) capacity&amp;#160;to constrain fossil fuel emissions to a sufficient extent has not yet been assessed.&amp;#160;The CO&lt;sub&gt;2&lt;/sub&gt; Monitoring Mission, planned as a constellation of satellites measuring&amp;#160;column-integrated atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration (XCO2),&amp;#160;is expected to become a key component of an MVS capacity.&amp;#160;&lt;/p&gt;&lt;p&gt;Here we provide an assessment of the potential of a Carbon Cycle Fossil Fuel Data&amp;#160;Assimilation System using synthetic XCO2 and other observations to constrain&amp;#160;fossil fuel CO&lt;sub&gt;2&lt;/sub&gt; emissions for an exemplary 1-week period in 2008.&amp;#160;We find that the system can provide useful weekly estimates of&amp;#160;country-scale fossil fuel emissions independent of national inventories. &amp;#160;When extrapolated from the weekly to the annual scale,&amp;#160;uncertainties in emissions are comparable to uncertainties in inventories,&amp;#160;so that estimates from inventories and from the MVS capacity can be used for&amp;#160;mutual verification.&amp;#160;&lt;/p&gt;&lt;p&gt;We further demonstrate an alternative, synergistic mode of operation,&amp;#160;which delivers a best emission estimate through assimilation of the inventory&amp;#160;information as an additional data stream. &amp;#160;We show the sensitivity of the results to the setup of the CCFFDAS and to&amp;#160;various aspects of the data streams that are assimilated, including&amp;#160;assessments of surface networks.&lt;/p&gt;

scholarly journals Methane Emissions from the Munich Oktoberfest

2019 ◽  
Author(s):  
Jia Chen ◽  
Florian Dietrich ◽  
Hossein Maazallahi ◽  
Andreas Forstmaier ◽  
Dominik Winkler ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Plume Dispersion ◽  
Emission Inventories ◽  
Ch4 Emissions ◽  
Policies And Measures ◽  
Future Emission ◽  
Gaussian Plume ◽  
Reduce Emissions ◽  
Limited Duration

Abstract. This study presents the first investigation of the methane (CH4) emissions of a big festival. In 2018 we measured the CH4 emissions of Munich Oktoberfest, the world's largest folk festival, using in-situ measurements combined with a Gaussian plume dispersion model. Oktoberfest is a potential source for CH4 as a high amount of natural gas for cooking and heating is used. Measurements were performed by walking and biking around the perimeter of the Oktoberfest premises (Theresienwiese) at different times of the day, during the week and at the weekend. The measurements show enhancements of up to 100 ppb compared to background values and measurements performed after Oktoberfest. The average emission flux of Oktoberfest is determined as 6.7 ± 0.6 μg/(m2s). Additional analyses, including the daily emission cycle and comparisons between emissions and the number of visitors, suggest that CH4 emissions of Oktoberfest are not only due to the human biogenic emissions; it is likely that fossil fuel CH4 emissions, such as incomplete combustion or loss in the gas appliances, are the major contributors to Oktoberfest emissions. Our results can help to develop CH4 reduction policies and measures to reduce emissions at festivals and other major events in cities. Furthermore, events with a limited duration have not yet been included in the state-of-the-art emission inventories, such as TNO-MACC, EDGAR or IER. Our investigations show that these emissions are not negligible. Therefore, these events should be included in future emission inventories.

scholarly journals Independent evaluation of point source fossil fuel CO2 emissions to better than 10%

2016 ◽  
Vol 113 (37) ◽  
pp. 10287-10291 ◽  
Author(s):  
Jocelyn Christine Turnbull ◽  
Elizabeth D. Keller ◽  
Margaret W. Norris ◽  
Rachael M. Wiltshire
Keyword(s):  
Point Source ◽  
Power Plants ◽  
Fossil Fuel ◽  
Transport Model ◽  
Sodium Hydroxide Solution ◽  
Time Integration ◽  
Emission Rates ◽  
Independent Evaluation ◽  
Atmospheric Observations ◽  
Better Than

Independent estimates of fossil fuel CO2 (CO2ff) emissions are key to ensuring that emission reductions and regulations are effective and provide needed transparency and trust. Point source emissions are a key target because a small number of power plants represent a large portion of total global emissions. Currently, emission rates are known only from self-reported data. Atmospheric observations have the potential to meet the need for independent evaluation, but useful results from this method have been elusive, due to challenges in distinguishing CO2ff emissions from the large and varying CO2 background and in relating atmospheric observations to emission flux rates with high accuracy. Here we use time-integrated observations of the radiocarbon content of CO2 (14CO2) to quantify the recently added CO2ff mole fraction at surface sites surrounding a point source. We demonstrate that both fast-growing plant material (grass) and CO2 collected by absorption into sodium hydroxide solution provide excellent time-integrated records of atmospheric 14CO2. These time-integrated samples allow us to evaluate emissions over a period of days to weeks with only a modest number of measurements. Applying the same time integration in an atmospheric transport model eliminates the need to resolve highly variable short-term turbulence. Together these techniques allow us to independently evaluate point source CO2ff emission rates from atmospheric observations with uncertainties of better than 10%. This uncertainty represents an improvement by a factor of 2 over current bottom-up inventory estimates and previous atmospheric observation estimates and allows reliable independent evaluation of emissions.

scholarly journals Temporal changes in the emissions of CH<sub>4</sub> and CO from China estimated from CH<sub>4</sub> / CO<sub>2</sub> and CO / CO<sub>2</sub> correlations observed at Hateruma Island

2013 ◽  
Vol 13 (8) ◽  
pp. 22893-22930 ◽  
Author(s):  
Y. Tohjima ◽  
M. Kubo ◽  
C. Minejima ◽  
H. Mukai ◽  
H. Tanimoto ◽  
...  
Keyword(s):  
Fossil Fuel ◽  
Dispersion Model ◽  
Temporal Changes ◽  
Particle Dispersion ◽  
Anthropogenic Sources ◽  
In Situ Observation ◽  
Mixing Ratios ◽  
Increasing Trend ◽  
Concentration Footprint

Abstract. In-situ observation of the atmospheric CO2, CH4, and CO mixing ratios at Hateruma Island (HAT, 24.05° N, 123.80° E) often show synoptic-scale variations with correlative elevations during winter, associated with air transport from the East Asian countries. We examine winter (November–March) trends in ΔCH4 / ΔCO2, ΔCO / ΔCO2, and ΔCO / ΔCH4 observed at Hateruma over the period 1999 to 2010. Although the ratios ΔCH4 / ΔCO2 and ΔCO / ΔCO2 both show an overall gradual decrease over the study period due to a recent rapid increase in fossil fuel consumption in China, we note that ΔCH4 / ΔCO2 and ΔCO / ΔCO2 remains relatively flat (no trend) during 2005–2010 and 1999–2004, respectively. The CO/CH4 slope on the other hand shows an increasing trend during 1999–2004 but a decrease during 2005–2010. Calculation of the concentration footprint for the atmospheric observation at HAT by using the FLEXPART Lagrangian particle dispersion model indicates that most of the short-term variations are caused by emission variations from North and East China. Combined with a set of reported emission maps, we have estimated the temporal changes in the annual CH4 and CO emissions from China under the assumption that the estimate of the fossil fuel-derived CO2 emissions based on the energy statistics is accurate. The estimated annual CH4 emissions, corresponding to non-seasonal sources or anthropogenic sources without rice fields, show a nearly constant value of 39 ± 6 TgCH4 yr−1 during 1998–2002, and then gradually increases to 46 ± 7 TgCH4 yr−1 in 2009/2010. The estimated annual CO emissions increase from 134 ± 26 TgCO yr−1 in 1998/1999 to 182 ± 33 TgCO yr−1 in 2004/2005, level off after 2005, and then slightly decrease to less than 160 TgCO yr−1 in 2008–2010.

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