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:During the summer of 2018, a widespread drought developed over Northern and Central Europe. The increase in temperature and the reduction of soil moisture have influenced carbon dioxide (CO2) exchange between the atmosphere and terrestrial ecosystems in various ways, such as a reduction of photosynthesis, changes in ecosystem respiration, or allowing more frequent fires. In this study, we characterize the resulting perturbation of the atmospheric CO2 seasonal cycles. 2018 has a good coverage of European regions affected by drought, allowing the investigation of how ecosystem flux anomalies impacted spatial CO2 gradients between stations. This density of stations is unprecedented compared to previous drought events in 2003 and 2015, particularly thanks to the deployment of the Integrated Carbon Observation System (ICOS) network of atmospheric greenhouse gas monitoring stations in recent years. Seasonal CO2 cycles from 48 European stations were available for 2017 and 2018. Earlier data were retrieved for comparison from international databases or national networks. Here, we show that the usual summer minimum in CO2 due to the surface carbon uptake was reduced by 1.4 ppm in 2018 for the 10 stations located in the area most affected by the temperature anomaly, mostly in Northern Europe. Notwithstanding, the CO2 transition phases before and after July were slower in 2018 compared to 2017, suggesting an extension of the growing season, with either continued CO2 uptake by photosynthesis and/or a reduction in respiration driven by the depletion of substrate for respiration inherited from the previous months due to the drought. For stations with sufficiently long time series, the CO2 anomaly observed in 2018 was compared to previous European droughts in 2003 and 2015. Considering the areas most affected by the temperature anomalies, we found a higher CO2 anomaly in 2003 (+3 ppm averaged over 4 sites), and a smaller anomaly in 2015 (+1 ppm averaged over 11 sites) compared to 2018. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

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

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.