Dataset Information

Assessing Lagrangian inverse modelling of urban anthropogenic CO₂ fluxes using in situ aircraft and ground-based measurements in the Tokyo area.

ABSTRACT:

Background

In order to use in situ measurements to constrain urban anthropogenic emissions of carbon dioxide (CO₂), we use a Lagrangian methodology based on diffusive backward trajectory tracer reconstructions and Bayesian inversion. The observations of atmospheric CO₂ were collected within the Tokyo Bay Area during the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) flights, from the Tsukuba tall tower of the Meteorological Research Institute (MRI) of the Japan Meteorological Agency and at two surface sites (Dodaira and Kisai) from the World Data Center for Greenhouse Gases (WDCGG).

Results

We produce gridded estimates of the CO₂ emissions and calculate the averages for different areas within the Kanto plain where Tokyo is located. Using these inversions as reference we investigate the impact of perturbing different elements in the inversion system. We modified the observations amount and location (surface only sparse vs. including aircraft CO₂ observations), the background representation, the wind data used to drive the transport model, the prior emissions magnitude and time resolution and error parameters of the inverse model.

Conclusions

Optimized fluxes were consistent with other estimates for the unperturbed simulations. Inclusion of CONTRAIL measurements resulted in significant differences in the magnitude of the retrieved fluxes, 13% on average for the whole domain and of up to 21% for the spatiotemporal cells with the highest fluxes. Changes in the background yielded differences in the retrieved fluxes of up to 50% and more. Simulated biases in the modelled transport cause differences in the retrieved fluxes of up to 30% similar to those obtained using different meteorological winds to advect the Lagrangian trajectories. Perturbations to the prior inventory can impact the fluxes by ~?10% or more depending on the assumptions on the error covariances. All of these factors can cause significant differences in the estimated flux, and highlight the challenges in estimating regional CO₂ fluxes from atmospheric observations.

SUBMITTER: Pisso I

PROVIDER: S-EPMC7227294 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Assessing Lagrangian inverse modelling of urban anthropogenic CO<sub>2</sub> fluxes using in situ aircraft and ground-based measurements in the Tokyo area.

Pisso Ignacio I Patra Prabir P Takigawa Masayuki M Machida Toshinobu T Matsueda Hidekazu H Sawa Yousuke Y

Carbon balance and management 20190517 1

<h4>Background</h4>In order to use in situ measurements to constrain urban anthropogenic emissions of carbon dioxide (CO<sub>2</sub>), we use a Lagrangian methodology based on diffusive backward trajectory tracer reconstructions and Bayesian inversion. The observations of atmospheric CO<sub>2</sub> were collected within the Tokyo Bay Area during the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) flights, from the Tsukuba tall tower of the Meteorological Research Institu ...[more]

PMID: 31101995

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Project description:The precise contribution of the two major sinks for anthropogenic CO2 emissions, terrestrial vegetation and the ocean, and their location and year-to-year variability are not well understood. Top-down estimates of the spatiotemporal variations in emissions and uptake of CO2 are expected to benefit from the increasing measurement density brought by recent in situ and remote CO2 observations. We uniquely apply a batch Bayesian synthesis inversion at relatively high resolution to in situ surface observations and bias-corrected GOSAT satellite column CO2 retrievals to deduce the global distributions of natural CO2 fluxes during 2009-2010. Our objectives include evaluating bottom-up prior flux estimates, assessing the value added by the satellite data, and examining the impacts of inversion technique and assumptions on posterior fluxes and uncertainties. The GOSAT inversion is generally better constrained than the in situ inversion, with smaller posterior regional flux uncertainties and correlations, because of greater spatial coverage, except over North America and high-latitude ocean. Complementarity of the in situ and GOSAT data enhances uncertainty reductions in a joint inversion; however, spatial and temporal gaps in sampling still limit the ability to accurately resolve fluxes down to the sub-continental scale. The GOSAT inversion produces a shift in the global CO2 sink from the tropics to the north and south relative to the prior, and an increased source in the tropics of ~2 Pg C y-1 relative to the in situ inversion, similar to what is seen in studies using other inversion approaches. This result may be driven by sampling and residual retrieval biases in the GOSAT data, as suggested by significant discrepancies between posterior CO2 distributions and surface in situ and HIPPO mission aircraft data. While the shift in the global sink appears to be a robust feature of the inversions, the partitioning of the sink between land and ocean in the inversions using either in situ or GOSAT data is found to be sensitive to prior uncertainties because of negative correlations in the flux errors. The GOSAT inversion indicates significantly less CO2 uptake in summer of 2010 than in 2009 across northern regions, consistent with the impact of observed severe heat waves and drought. However, observations from an in situ network in Siberia imply that the GOSAT inversion exaggerates the 2010-2009 difference in uptake in that region, while the prior CASA-GFED model of net ecosystem production and fire emissions reasonably estimates that quantity. The prior, in situ posterior, and GOSAT posterior all indicate greater uptake over North America in spring to early summer of 2010 than in 2009, consistent with wetter conditions. The GOSAT inversion does not show the expected impact on fluxes of a 2010 drought in the Amazon; evaluation of posterior mole fractions against local aircraft profiles suggests that time-varying GOSAT coverage can bias estimation of flux interannual variability in this region.

Dataset Information

Assessing Lagrangian inverse modelling of urban anthropogenic CO₂ fluxes using in situ aircraft and ground-based measurements in the Tokyo area.

Background

Results

Conclusions

Publications

Assessing Lagrangian inverse modelling of urban anthropogenic CO<sub>2</sub> fluxes using in situ aircraft and ground-based measurements in the Tokyo area.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

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Dataset Information

Assessing Lagrangian inverse modelling of urban anthropogenic CO2 fluxes using in situ aircraft and ground-based measurements in the Tokyo area.

Background

Results

Conclusions

Publications

Assessing Lagrangian inverse modelling of urban anthropogenic CO<sub>2</sub> fluxes using in situ aircraft and ground-based measurements in the Tokyo area.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Assessing Lagrangian inverse modelling of urban anthropogenic CO₂ fluxes using in situ aircraft and ground-based measurements in the Tokyo area.