Dataset Information

Detection of Anthropogenic CO₂ Emission Signatures with TanSat CO₂ and with Copernicus Sentinel-5 Precursor (S5P) NO₂ Measurements: First Results.

ABSTRACT: China's first carbon dioxide (CO₂) measurement satellite mission, TanSat, was launched in December 2016. This paper introduces the first attempt to detect anthropogenic CO₂ emission signatures using CO₂ observations from TanSat and NO₂ measurements from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S5P) satellite. We focus our analysis on two selected cases in Tangshan, China and Tokyo, Japan. We found that the TanSat XCO₂ measurements have the capability to capture the anthropogenic variations in the plume and have spatial patterns similar to that of the TROPOMI NO₂ observations. The linear fit between TanSat XCO₂ and TROPOMI NO₂ indicates the CO₂-to-NO₂ ratio of 0.8 × 10^-16 ppm (molec cm^-2)^-1 in Tangshan and 2.3 × 10^-16 ppm (molec cm^-2)^-1 in Tokyo. Our results align with the CO₂-to-NO _x emission ratios obtained from the EDGAR v6 emission inventory.

SUBMITTER: Yang D

PROVIDER: S-EPMC9592547 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Detection of Anthropogenic CO2 Emission Signatures with TanSat CO2 and with Copernicus Sentinel-5 Precursor (S5P) NO2 Measurements: First Results.

Yang Dongxu D Hakkarainen Janne J Liu Yi Y Ialongo Iolanda I Cai Zhaonan Z Tamminen Johanna J

Advances in atmospheric sciences 20221025 1

China's first carbon dioxide (CO2) measurement satellite mission, TanSat, was launched in December 2016. This paper introduces the first attempt to detect anthropogenic CO2 emission signatures using CO2 observations from TanSat and NO2 measurements from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S5P) satellite. We focus our analysis on two selected cases in Tangshan, China and Tokyo, Japan. We found th ...[more]

PMID: 36312903

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Project description:BackgroundIn 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).ResultsWe 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.ConclusionsOptimized 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.

Project description:The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a global high-spatial resolution gridded emission data product that distributes carbon dioxide (CO2) emissions from fossil fuel combustion. The emission spatial distributions are estimated at a 1×1 km spatial resolution over land using power plant profiles (emission intensity and geographical location) and satellite-observed nighttime lights. This paper describes the year 2016 version of the ODIAC emission data product (ODIAC2016) and presents analyses that help guiding data users, especially for atmospheric CO2 tracer transport simulations and flux inversion analysis. Since the original publication in 2011, we have made modifications to our emission modeling framework in order to deliver a comprehensive global gridded emission data product. Major changes from the 2011 publication are 1) the use of emissions estimates made by the Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory (ORNL) by fuel type (solid, liquid, gas, cement manufacturing, gas flaring and international aviation and marine bunkers), 2) the use of multiple spatial emission proxies by fuel type such as nightlight data specific to gas flaring and ship/aircraft fleet tracks and 3) the inclusion of emission temporal variations. Using global fuel consumption data, we extrapolated the CDIAC emissions estimates for the recent years and produced the ODIAC2016 emission data product that covers 2000-2015. Our emission data can be viewed as an extended version of CDIAC gridded emission data product, which should allow data users to impose global fossil fuel emissions in more comprehensive manner than original CDIAC product. Our new emission modeling framework allows us to produce future versions of ODIAC emission data product with a timely update. Such capability has become more significant given the CDIAC/ORNL's shutdown. ODIAC data product could play an important role to support carbon cycle science, especially modeling studies with space-based CO2 data collected near real time by ongoing carbon observing missions such as Japanese Greenhouse Observing SATellite (GOSAT), NASA's Orbiting Carbon Observatory 2 (OCO-2) and upcoming future missions. The ODIAC emission data product including the latest version of the ODIAC emission data (ODIAC2017, 2000-2016), is distributed from http://db.cger.nies.go.jp/dataset/ODIAC/ with a DOI.

Dataset Information

Detection of Anthropogenic CO₂ Emission Signatures with TanSat CO₂ and with Copernicus Sentinel-5 Precursor (S5P) NO₂ Measurements: First Results.

Publications

Detection of Anthropogenic CO<sub>2</sub> Emission Signatures with TanSat CO<sub>2</sub> and with Copernicus Sentinel-5 Precursor (S5P) NO<sub>2</sub> Measurements: First Results.

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