scholarly journals Quantifying sources of Brazil's CH<sub>4</sub> emissions between 2010 and 2018 from satellite data

2020 ◽  
Author(s):  
Rachel L. Tunnicliffe ◽  
Anita L. Ganesan ◽  
Robert J. Parker ◽  
Hartmut Boesch ◽  
Nicola Gedney ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Satellite Data ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Satellite Measurements ◽  
Ch4 Emissions ◽  
Surface Data ◽  
Sensitivity Studies ◽  
Using Data ◽  
Gosat Satellite

Abstract. Brazil's CH4 emissions over the period 2010–2018 were derived for the three main sectors of activity: anthropogenic, wetland and biomass burning. Our inverse modelling estimates were derived from GOSAT satellite measurements of XCH4 combined with surface data from Ragged Point, Barbados and the high-resolution regional atmospheric transport model NAME. We find that Brazil's mean emissions over 2010–2018 are 33.6 ± 3.6 Tg/yr, which are comprised of 19.0 ± 2.6 Tg/yr from anthropogenic (primarily related to agriculture and waste), 13.0 ± 1.9 Tg/yr from wetlands and 1.7 ± 0.3 Tg/yr from biomass burning sources. In addition, between the 2011–2013 and 2014–2018 periods, Brazil's mean emissions rose by 6.9 ± 5.3 Tg/yr and this increase may have contributed to the accelerated global methane growth rate observed during the latter period. We find that wetland emissions from the Western Amazon increased during the start of the 2015–16 El Nino by 3.7 ± 2.7 Tg/yr and this is likely driven by increased surface temperatures. We also find that our estimates of anthropogenic emissions are consistent with those reported by Brazil to the United Framework Convention on Climate Change. We show that satellite data is beneficial for constraining national-scale CH4 emissions, and, through a series of sensitivity studies and validation experiments using data not assimilated in the inversion, we demonstrate that calibrated ground-based data are important to include alongside satellite data in a regional inversion, and that inversions must account for any offsets between the two data streams and their representations by models.

scholarly journals Quantifying sources of Brazil's CH<sub>4</sub> emissions between 2010 and 2018 from satellite data

2020 ◽  
Vol 20 (21) ◽  
pp. 13041-13067
Author(s):  
Rachel L. Tunnicliffe ◽  
Anita L. Ganesan ◽  
Robert J. Parker ◽  
Hartmut Boesch ◽  
Nicola Gedney ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Satellite Data ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Atmospheric Dispersion ◽  
Ch4 Emissions ◽  
Surface Data ◽  
Sensitivity Studies ◽  
Modelling Environment ◽  
Using Data

Abstract. Brazil's CH4 emissions over the period 2010–2018 were derived for the three main sectors of activity: anthropogenic, wetland and biomass burning. Our inverse modelling estimates were derived from GOSAT (Greenhouse gases Observing SATellite) satellite measurements of XCH4 combined with surface data from Ragged Point, Barbados, and the high-resolution regional atmospheric transport model NAME (Numerical Atmospheric-dispersion Modelling Environment). We find that Brazil's mean emissions over 2010–2018 are 33.6±3.6Tgyr-1, which are comprised of 19.0±2.6Tgyr-1 from anthropogenic (primarily related to agriculture and waste), 13.0±1.9Tgyr-1 from wetlands and 1.7±0.3Tgyr-1 from biomass burning sources. In addition, between the 2011–2013 and 2014–2018 periods, Brazil's mean emissions rose by 6.9±5.3Tgyr-1 and this increase may have contributed to the accelerated global methane growth rate observed during the latter period. We find that wetland emissions from the western Amazon increased during the start of the 2015–2016 El Niño by 3.7±2.7Tgyr-1 and this is likely driven by increased surface temperatures. We also find that our estimates of anthropogenic emissions are consistent with those reported by Brazil to the United Framework Convention on Climate Change. We show that satellite data are beneficial for constraining national-scale CH4 emissions, and, through a series of sensitivity studies and validation experiments using data not assimilated in the inversion, we demonstrate that (a) calibrated ground-based data are important to include alongside satellite data in a regional inversion and that (b) inversions must account for any offsets between the two data streams and their representations by models.

scholarly journals Influences of hydroxyl radicals (OH) on top-down estimates of the global and regional methane budgets

2020 ◽  
Author(s):  
Yuanhong Zhao ◽  
Marielle Saunois ◽  
Philippe Bousquet ◽  
Xin Lin ◽  
Antoine Berchet ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Climate Models ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Temporal Variations ◽  
Oh Radicals ◽  
Chemical Transport Model ◽  
Top Down ◽  
Ch4 Emissions ◽  
The Impact

Abstract. The hydroxyl radical (OH), which is the dominant sink of methane (CH4), plays a key role to close the global methane budget. Previous research that assessed the impact of OH changes on the CH4 budget mostly relied on box modeling inversions with a very simplified atmospheric transport and no representation of the heterogeneous spatial distribution of OH radicals. Here using a variational Bayesian inversion framework and a 3D chemical transport model, LMDz, combined with 10 different OH fields derived from chemistry-climate models (CCMI experiment), we evaluate the influence of OH burden, spatial distribution, and temporal variations on the global CH4 budget. The global tropospheric mean CH4-reaction-weighted [OH] ([OH]GM-CH4) ranges 10.3–16.3 × 105 molec cm−3 across 10 OH fields during the early 2000s, resulting in inversion-based global CH4 emissions between 518 and 757 Tg yr−1. The uncertainties in CH4 inversions induced by the different OH fields are comparable to, or even larger than the uncertainty typically given by bottom-up and top-down estimates. Based on the LMDz inversions, we estimate that a 1 %-increase in OH burden leads to an increase of 4 Tg yr−1 in the estimate of global methane emissions, which is about 25 % smaller than what is estimated by box-models. The uncertainties in emissions induced by OH are largest over South America, corresponding to large inter-model differences of [OH] in this region. From the early to the late 2000s, the optimized CH4 emissions increased by 21.9 ± 5.7 Tg yr−1 (16.6–30.0 Tg yr−1), of which ~ 25 % (on average) is contributed by −0.5 to +1.8 % increase in OH burden. If the CCMI models represent the OH trend properly over the 2000s, our results show that a higher increasing trend of CH4 emissions is needed to match the CH4 observations compared to the CH4 emission trend derived using constant OH. This study strengthens the importance to reach a better representation of OH burden and of OH spatial and temporal distributions to reduce the uncertainties on the global CH4 budget.

scholarly journals The importance of transport model uncertainties for the estimation of CO<sub>2</sub> sources and sinks using satellite measurements

2010 ◽  
Vol 10 (20) ◽  
pp. 9981-9992 ◽  
Author(s):  
S. Houweling ◽  
I. Aben ◽  
F.-M. Breon ◽  
F. Chevallier ◽  
N. Deutscher ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
A Priori ◽  
Model Errors ◽  
Tracer Transport ◽  
Satellite Measurements ◽  
Transport Models ◽  
Sources And Sinks ◽  
The Impact ◽  
Ppm Level

Abstract. This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common a priori CO2 fluxes and initial concentrations. Forward simulations of column averaged CO2 (xCO2) mixing ratios vary between the models by σ=0.5 ppm over the continents and σ=0.27 ppm over the oceans. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 PgC/yr per 106 km2 over land and 0.03 PgC/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 PgC/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. A variable, but overall encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen, although systematic differences are found exceeding the 0.5 ppm level. Because of this, our estimate of the impact of transport model uncerainty is likely to be conservative. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Improving the accuracy of these models should receive high priority, which calls for a closer collaboration between experts in atmospheric dynamics and tracer transport.

scholarly journals Global lightning NO<sub>x</sub> production estimated by an assimilation of multiple satellite data sets

2014 ◽  
Vol 14 (7) ◽  
pp. 3277-3305 ◽  
Author(s):  
K. Miyazaki ◽  
H. J. Eskes ◽  
K. Sudo ◽  
C. Zhang
Keyword(s):  
Satellite Data ◽  
Production Efficiency ◽  
Transport Model ◽  
Chemical System ◽  
No Production ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Independent Observations ◽  
Sensitivity Studies

Abstract. The global source of lightning-produced NOx (LNOx) is estimated by assimilating observations of NO2, O3, HNO3, and CO measured by multiple satellite measurements into a chemical transport model. Included are observations from the Ozone Monitoring Instrument (OMI), Microwave Limb Sounder (MLS), Tropospheric Emission Spectrometer (TES), and Measurements of Pollution in the Troposphere (MOPITT) instruments. The assimilation of multiple chemical data sets with different vertical sensitivity profiles provides comprehensive constraints on the global LNOx source while improving the representations of the entire chemical system affecting atmospheric NOx, including surface emissions and inflows from the stratosphere. The annual global LNOx source amount and NO production efficiency are estimated at 6.3 Tg N yr−1 and 310 mol NO flash−1, respectively. Sensitivity studies with perturbed satellite data sets, model and data assimilation settings lead to an error estimate of about 1.4 Tg N yr−1 on this global LNOx source. These estimates are significantly different from those estimated from a parameter inversion that optimizes only the LNOx source from NO2 observations alone, which may lead to an overestimate of the source adjustment. The total LNOx source is predominantly corrected by the assimilation of OMI NO2 observations, while TES and MLS observations add important constraints on the vertical source profile. The results indicate that the widely used lightning parameterization based on the C-shape assumption underestimates the source in the upper troposphere and overestimates the peak source height by up to about 1 km over land and the tropical western Pacific. Adjustments are larger over ocean than over land, suggesting that the cloud height dependence is too weak over the ocean in the Price and Rind (1992) approach. The significantly improved agreement between the analyzed ozone fields and independent observations gives confidence in the performance of the LNOx source estimation.

scholarly journals Top-down estimates of black carbon emissions at high latitudes using an atmospheric transport model and a Bayesian inversion framework

2018 ◽  
Vol 18 (20) ◽  
pp. 15307-15327 ◽  
Author(s):  
Nikolaos Evangeliou ◽  
Rona L. Thompson ◽  
Sabine Eckhardt ◽  
Andreas Stohl
Keyword(s):  
North America ◽  
Biomass Burning ◽  
Oil And Gas ◽  
Transport Model ◽  
Atmospheric Transport ◽  
A Priori ◽  
Gas Production ◽  
Anthropogenic Sources ◽  
A Posteriori ◽  
Northern Latitudes

Abstract. This paper presents the results of BC inversions at high northern latitudes (> 50° N) for the 2013–2015 period. A sensitivity analysis was performed to select the best representative species for BC and the best a priori emission dataset. The same model ensemble was used to assess the uncertainty of the a posteriori emissions of BC due to scavenging and removal and due to the use of different a priori emission inventory. A posteriori concentrations of BC simulated over Arctic regions were compared with independent observations from flight and ship campaigns showing, in all cases, smaller bias, which in turn witnesses the success of the inversion. The annual a posteriori emissions of BC at latitudes above 50° N were estimated as 560±171 kt yr−1, significantly smaller than in ECLIPSEv5 (745 kt yr−1), which was used and the a priori information in the inversions of BC. The average relative uncertainty of the inversions was estimated to be 30 %.A posteriori emissions of BC in North America are driven by anthropogenic sources, while biomass burning appeared to be less significant as it is also confirmed by satellite products. In northern Europe, a posteriori emissions were estimated to be half compared to the a priori ones, with the highest releases to be in megacities and due to biomass burning in eastern Europe. The largest emissions of BC in Siberia were calculated along the transect between Yekaterinsburg and Chelyabinsk. The optimised emissions of BC were high close to the gas flaring regions in Russia and in western Canada (Alberta), where numerous power and oil and gas production industries operate. Flaring emissions in Nenets–Komi oblast (Russia) were estimated to be much lower than in the a priori emissions, while in Khanty-Mansiysk (Russia) they remained the same after the inversions of BC. Increased emissions at the borders between Russia and Mongolia are probably due to biomass burning in villages along the Trans-Siberian Railway. The maximum BC emissions in high northern latitudes (> 50° N) were calculated for summer months due to biomass burning and they are controlled by seasonal variations in Europe and Asia, while North America showed a much smaller variability.

scholarly journals Top–down estimates of black carbon emissions at high latitudes using an atmospheric transport model and a Bayesian inversion framework

2018 ◽  
Author(s):  
Nikolaos Evangeliou ◽  
Rona L. Thompson ◽  
Sabine Eckhardt ◽  
Andreas Stohl
Keyword(s):  
Biomass Burning ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Gas Production ◽  
Anthropogenic Sources ◽  
Arctic Regions ◽  
Northern Latitudes ◽  
Representative Species ◽  
Independent Observations ◽  
Oil Gas

Abstract. This paper presents the results of BC inversions at high northern latitudes (> 50° N) for the 2013–2015 period. A sensitivity analysis was performed to select the best representative species for BC and the best prior emission dataset. The same model ensemble was used to assess the uncertainty of the posterior emissions of BC due to scavenging and removal and due to the use of different prior emission inventory. The optimised emissions of BC were high close to the gas flaring regions in Russia and in Western Canada (Alberta), where numerous power and oil/gas production industries operate. The annual posterior emissions of BC at latitudes above 50° N were estimated as 560 ± 171 kt yr−1, significantly smaller than in ECLIPSEv5 (745 kt yr−1), which was used and the prior information in the inversions of BC. The average relative uncertainty of the inversions was estimated to be 30 %. Posterior concentrations of BC simulated over Arctic regions were compared with independent observations from flight and ship campaigns showing, in all cases, smaller bias, which in turn witnesses the success of the inversion. Posterior emissions of BC in North America are driven by anthropogenic sources, while biomass burning appeared to be less significant as it is also confirmed by satellite products. In North Europe, posterior emissions were estimated to be half compared to the prior ones, with the highest releases to be in megacities and due to biomass burning in Eastern Europe. The largest emissions of BC in Siberia were calculated along the transect between Yekaterinsburg and Chelyabinsk. Flaring emissions in Nenets-Komi oblast (Russia) were estimated to be much lower than in the prior emissions, while in Khanty-Mansiysk (Russia) they remained the same after the inversions of BC. Increased emissions in the borders between Russia and Mongolia are probably due to biomass burning in villages along the Trans-Siberian Railway.

scholarly journals Global methane emission estimates for 2000–2012 from CarbonTracker Europe-CH<sub>4</sub> v1.0

2017 ◽  
Vol 10 (3) ◽  
pp. 1261-1289 ◽  
Author(s):  
Aki Tsuruta ◽  
Tuula Aalto ◽  
Leif Backman ◽  
Janne Hakkarainen ◽  
Ingrid T. van der Laan-Luijkx ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
The United States ◽  
Total Carbon ◽  
Ch4 Emissions ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. We present a global distribution of surface methane (CH4) emission estimates for 2000–2012 derived using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, anthropogenic and biospheric CH4 emissions are simultaneously estimated based on constraints of global atmospheric in situ CH4 observations. The system was configured to either estimate only anthropogenic or biospheric sources per region, or to estimate both categories simultaneously. The latter increased the number of optimizable parameters from 62 to 78. In addition, the differences between two numerical schemes available to perform turbulent vertical mixing in the atmospheric transport model TM5 were examined. Together, the system configurations encompass important axes of uncertainty in inversions and allow us to examine the robustness of the flux estimates. The posterior emission estimates are further evaluated by comparing simulated atmospheric CH4 to surface in situ observations, vertical profiles of CH4 made by aircraft, remotely sensed dry-air total column-averaged mole fraction (XCH4) from the Total Carbon Column Observing Network (TCCON), and XCH4 from the Greenhouse gases Observing Satellite (GOSAT). The evaluation with non-assimilated observations shows that posterior XCH4 is better matched with the retrievals when the vertical mixing scheme with faster interhemispheric exchange is used. Estimated posterior mean total global emissions during 2000–2012 are 516 ± 51 Tg CH4 yr−1, with an increase of 18 Tg CH4 yr−1 from 2000–2006 to 2007–2012. The increase is mainly driven by an increase in emissions from South American temperate, Asian temperate and Asian tropical TransCom regions. In addition, the increase is hardly sensitive to different model configurations ( <  2 Tg CH4 yr−1 difference), and much smaller than suggested by EDGAR v4.2 FT2010 inventory (33 Tg CH4 yr−1), which was used for prior anthropogenic emission estimates. The result is in good agreement with other published estimates from inverse modelling studies (16–20 Tg CH4 yr−1). However, this study could not conclusively separate a small trend in biospheric emissions (−5 to +6.9 Tg CH4 yr−1) from the much larger trend in anthropogenic emissions (15–27 Tg CH4 yr−1). Finally, we find that the global and North American CH4 balance could be closed over this time period without the previously suggested need to strongly increase anthropogenic CH4 emissions in the United States. With further developments, especially on the treatment of the atmospheric CH4 sink, we expect the data assimilation system presented here will be able to contribute to the ongoing interpretation of changes in this important greenhouse gas budget.

scholarly journals The importance of transport model uncertainties for the estimation of CO<sub>2</sub> sources and sinks using satellite measurements

2010 ◽  
Vol 10 (6) ◽  
pp. 14737-14769 ◽  
Author(s):  
S. Houweling ◽  
I. Aben ◽  
F.-M. Breon ◽  
F. Chevallier ◽  
N. Deutscher ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Model Errors ◽  
Satellite Measurements ◽  
Transport Models ◽  
Sources And Sinks ◽  
Remote Sensing Technique ◽  
Mixing Ratios ◽  
Further Development ◽  
Ppm Level

Abstract. This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common CO2 fluxes and initial concentrations. Simulated column averaged CO2 (xCO2) mixing ratios vary between the models by σ=0.5 ppm over the continents and σ=0.27 ppm over sea. A variable, but overall quite encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 Pg C/yr per 106 km2 over land and 0.03 Pg C/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 Pg C/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Further development of these models should receive high priority.

scholarly journals The Environmental Effects of the April 2020 Wildfires and the Cs-137 Re-Suspension in the Chernobyl Exclusion Zone: A Multi-Hazard Threat

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 467
Author(s):  
Rocío Baró ◽  
Christian Maurer ◽  
Jerome Brioude ◽  
Delia Arnold ◽  
Marcus Hirtl
Keyword(s):  
Air Quality ◽  
Nuclear Power ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Point Of View ◽  
Plume Dispersion ◽  
Exclusion Zone ◽  
Fire Plume ◽  
Mean Values ◽  
The Impact

This paper demonstrates the environmental impacts of the wildfires occurring at the beginning of April 2020 in and around the highly contaminated Chernobyl Exclusion Zone (CEZ). Due to the critical fire location, concerns arose about secondary radioactive contamination potentially spreading over Europe. The impact of the fire was assessed through the evaluation of fire plume dispersion and re-suspension of the radionuclide Cs-137, whereas, to assess the smoke plume effect, a WRF-Chem simulation was performed and compared to Tropospheric Monitoring Instrument (TROPOMI) satellite columns. The results show agreement of the simulated black carbon and carbon monoxide plumes with the plumes as observed by TROPOMI, where pollutants were also transported to Belarus. From an air quality and health perspective, the wildfires caused extremely bad air quality over Kiev, where the WRF-Chem model simulated mean values of PM2.5 up to 300 µg/m3 (during the first fire outbreak) over CEZ. The re-suspension of Cs-137 was assessed by a Bayesian inverse modelling approach using FLEXPART as the atmospheric transport model and Ukraine observations, yielding a total release of 600 ± 200 GBq. The increase in both smoke and Cs-137 emissions was only well correlated on the 9 April, likely related to a shift of the focus area of the fires. From a radiological point of view even the highest Cs-137 values (average measured or modelled air concentrations and modelled deposition) at the measurement site closest to the Chernobyl Nuclear Power Plant, i.e., Kiev, posed no health risk.

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