Articles | Volume 16, issue 12
https://doi.org/10.5194/acp-16-7743-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-7743-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
What would dense atmospheric observation networks bring to the quantification of city CO2 emissions?
Lin Wu
CORRESPONDING AUTHOR
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR
CEA-CNRS-UVSQ, Gif sur Yvette, France
Grégoire Broquet
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR
CEA-CNRS-UVSQ, Gif sur Yvette, France
Philippe Ciais
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR
CEA-CNRS-UVSQ, Gif sur Yvette, France
Valentin Bellassen
CDC Climat, 75009 Paris, France
now at: INRA, UMR 1041 CESAER, 21000 Dijon, France
Felix Vogel
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR
CEA-CNRS-UVSQ, Gif sur Yvette, France
Frédéric Chevallier
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR
CEA-CNRS-UVSQ, Gif sur Yvette, France
Irène Xueref-Remy
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR
CEA-CNRS-UVSQ, Gif sur Yvette, France
Yilong Wang
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), UMR
CEA-CNRS-UVSQ, Gif sur Yvette, France
Viewed
Total article views: 4,690 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 05 Nov 2015)
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
2,618 | 1,672 | 400 | 4,690 | 437 | 108 | 116 |
- HTML: 2,618
- PDF: 1,672
- XML: 400
- Total: 4,690
- Supplement: 437
- BibTeX: 108
- EndNote: 116
Total article views: 3,913 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 24 Jun 2016)
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
2,263 | 1,273 | 377 | 3,913 | 263 | 89 | 94 |
- HTML: 2,263
- PDF: 1,273
- XML: 377
- Total: 3,913
- Supplement: 263
- BibTeX: 89
- EndNote: 94
Total article views: 777 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 05 Nov 2015)
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
355 | 399 | 23 | 777 | 174 | 19 | 22 |
- HTML: 355
- PDF: 399
- XML: 23
- Total: 777
- Supplement: 174
- BibTeX: 19
- EndNote: 22
Cited
45 citations as recorded by crossref.
- Local Anomalies in the Column‐Averaged Dry Air Mole Fractions of Carbon Dioxide Across the Globe During the First Months of the Coronavirus Recession F. Chevallier et al. 10.1029/2020GL090244
- Constraining Urban CO2 Emissions Using Mobile Observations from a Light Rail Public Transit Platform D. Mallia et al. 10.1021/acs.est.0c04388
- CO2 and Carbon Emissions from Cities: Linkages to Air Quality, Socioeconomic Activity, and Stakeholders in the Salt Lake City Urban Area J. Lin et al. 10.1175/BAMS-D-17-0037.1
- Simulating estimation of California fossil fuel and biosphere carbon dioxide exchanges combining in situ tower and satellite column observations M. Fischer et al. 10.1002/2016JD025617
- A High-Resolution Monitoring Approach of Urban Co2 Fluxes. Part 2 - Optimisation Framework Using Eddy Covariance Observations S. Stagakis et al. 10.2139/ssrn.4172740
- Tall tower eddy covariance measurements of CO2 fluxes in Vienna, Austria B. Matthews & H. Schume 10.1016/j.atmosenv.2022.118941
- Evaluation and environmental correction of ambient CO<sub>2</sub> measurements from a low-cost NDIR sensor C. Martin et al. 10.5194/amt-10-2383-2017
- Comment F. Chevallier & F. Bréon 10.1080/01621459.2017.1419138
- Integrated urban services: Experience from four cities on different continents A. Baklanov et al. 10.1016/j.uclim.2020.100610
- Detection of fossil fuel emission trends in the presence of natural carbon cycle variability Y. Yin et al. 10.1088/1748-9326/ab2dd7
- Lagrangian inversion of anthropogenic CO2 emissions from Beijing using differential column measurements K. Che et al. 10.1088/1748-9326/ac7477
- Comparison of OCO-2 target observations to MUCCnet – is it possible to capture urban XCO2 gradients from space? M. Rißmann et al. 10.5194/amt-15-6605-2022
- Assessing the Effectiveness of an Urban CO2 Monitoring Network over the Paris Region through the COVID-19 Lockdown Natural Experiment J. Lian et al. 10.1021/acs.est.1c04973
- Development of a regional carbon assimilation system and its application for estimating fossil fuel carbon emissions in the Yangtze River Delta, China Z. Zhang et al. 10.1016/j.scitotenv.2024.177720
- The first 1-year-long estimate of the Paris region fossil fuel CO<sub>2</sub> emissions based on atmospheric inversion J. Staufer et al. 10.5194/acp-16-14703-2016
- Characterization of a commercial lower-cost medium-precision non-dispersive infrared sensor for atmospheric CO<sub>2</sub> monitoring in urban areas E. Arzoumanian et al. 10.5194/amt-12-2665-2019
- Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties K. Wu et al. 10.1525/elementa.138
- Complementing XCO2 imagery with ground-based CO2 and 14CO2 measurements to monitor CO2 emissions from fossil fuels on a regional to local scale E. Potier et al. 10.5194/amt-15-5261-2022
- Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL S. Vardag & R. Maiwald 10.5194/gmd-17-1885-2024
- Bayesian Optimization of the Community Land Model Simulated Biosphere–Atmosphere Exchange using CO2 Observations from a Dense Tower Network and Aircraft Campaigns over Oregon A. Schmidt et al. 10.1175/EI-D-16-0011.1
- Carbon dioxide, methane and nitrous oxide emissions from the human-impacted Seine watershed in France A. Marescaux et al. 10.1016/j.scitotenv.2018.06.151
- Sustained Reductions of Bay Area CO2 Emissions 2018–2022 N. Asimow et al. 10.1021/acs.est.3c09642
- Development and deployment of a mid-cost CO2 sensor monitoring network to support atmospheric inverse modeling for quantifying urban CO2 emissions in Paris J. Lian et al. 10.5194/amt-17-5821-2024
- Designing additional CO2 in-situ surface observation networks over South Korea using bayesian inversion coupled with Lagrangian modelling S. Takele Kenea et al. 10.1016/j.atmosenv.2024.120471
- Estimates of CO<sub>2</sub> fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling A. Nickless et al. 10.5194/acp-18-4765-2018
- Estimates of Anthropogenic CO2 Emissions for Moscow and St. Petersburg Based on OCO-2 Satellite Measurements Y. Timofeev et al. 10.1134/S1024856020060238
- The BErkeley Atmospheric CO<sub>2</sub> Observation Network: initial evaluation A. Shusterman et al. 10.5194/acp-16-13449-2016
- Comparison of Global Downscaled Versus Bottom‐Up Fossil Fuel CO2 Emissions at the Urban Scale in Four U.S. Urban Areas K. Gurney et al. 10.1029/2018JD028859
- Evaluation of light atmospheric plume inversion methods using synthetic XCO2 satellite images to compute Paris CO2 emissions A. Danjou et al. 10.1016/j.rse.2023.113900
- Analysis of anthropogenic CO2 emission uncertainty and influencing factors at city scale in Yangtze River Delta region: One of the world's largest emission hotspots H. Liu et al. 10.1016/j.apr.2024.102281
- Optimal design of surface CO2 observation network to constrain China’s land carbon sink Y. Wang et al. 10.1016/j.scib.2023.07.010
- Site selection and effects of background towers on urban CO2 estimates: A case study from central downtown Zhengzhou in China G. Ren et al. 10.1016/j.envres.2024.120169
- A high-resolution monitoring approach of urban CO2 fluxes. Part 2 – surface flux optimisation using eddy covariance observations S. Stagakis et al. 10.1016/j.scitotenv.2023.166035
- Evaluation of Low-Cost CO2 Sensors Using Reference Instruments and Standard Gases for Indoor Use Q. Cai et al. 10.3390/s24092680
- Analysis of temporal and spatial variability of atmospheric CO<sub>2</sub> concentration within Paris from the GreenLITE™ laser imaging experiment J. Lian et al. 10.5194/acp-19-13809-2019
- Network design for quantifying urban CO<sub>2</sub> emissions: assessing trade-offs between precision and network density A. Turner et al. 10.5194/acp-16-13465-2016
- An atmospheric inversion over the city of Cape Town: sensitivity analyses A. Nickless et al. 10.5194/acp-19-7789-2019
- Can we use atmospheric CO2 measurements to verify emission trends reported by cities? Lessons from a 6-year atmospheric inversion over Paris J. Lian et al. 10.5194/acp-23-8823-2023
- Diagnostic methods for atmospheric inversions of long-lived greenhouse gases A. Michalak et al. 10.5194/acp-17-7405-2017
- Sensitivity to the sources of uncertainties in the modeling of atmospheric CO<sub>2</sub> concentration within and in the vicinity of Paris J. Lian et al. 10.5194/acp-21-10707-2021
- Analysis of total column CO<sub>2</sub> and CH<sub>4</sub> measurements in Berlin with WRF-GHG X. Zhao et al. 10.5194/acp-19-11279-2019
- Diurnal, synoptic and seasonal variability of atmospheric CO<sub>2</sub> in the Paris megacity area I. Xueref-Remy et al. 10.5194/acp-18-3335-2018
- A city-level comparison of fossil-fuel and industry processes-induced CO2 emissions over the Beijing-Tianjin-Hebei region from eight emission inventories P. Han et al. 10.1186/s13021-020-00163-2
- A Method for Estimating the Background Column Concentration of CO2 Using the Lagrangian Approach Z. Pei et al. 10.1109/TGRS.2022.3176134
- Analysis of the potential of near-ground measurements of CO<sub>2</sub> and CH<sub>4</sub> in London, UK, for the monitoring of city-scale emissions using an atmospheric transport model A. Boon et al. 10.5194/acp-16-6735-2016
44 citations as recorded by crossref.
- Local Anomalies in the Column‐Averaged Dry Air Mole Fractions of Carbon Dioxide Across the Globe During the First Months of the Coronavirus Recession F. Chevallier et al. 10.1029/2020GL090244
- Constraining Urban CO2 Emissions Using Mobile Observations from a Light Rail Public Transit Platform D. Mallia et al. 10.1021/acs.est.0c04388
- CO2 and Carbon Emissions from Cities: Linkages to Air Quality, Socioeconomic Activity, and Stakeholders in the Salt Lake City Urban Area J. Lin et al. 10.1175/BAMS-D-17-0037.1
- Simulating estimation of California fossil fuel and biosphere carbon dioxide exchanges combining in situ tower and satellite column observations M. Fischer et al. 10.1002/2016JD025617
- A High-Resolution Monitoring Approach of Urban Co2 Fluxes. Part 2 - Optimisation Framework Using Eddy Covariance Observations S. Stagakis et al. 10.2139/ssrn.4172740
- Tall tower eddy covariance measurements of CO2 fluxes in Vienna, Austria B. Matthews & H. Schume 10.1016/j.atmosenv.2022.118941
- Evaluation and environmental correction of ambient CO<sub>2</sub> measurements from a low-cost NDIR sensor C. Martin et al. 10.5194/amt-10-2383-2017
- Comment F. Chevallier & F. Bréon 10.1080/01621459.2017.1419138
- Integrated urban services: Experience from four cities on different continents A. Baklanov et al. 10.1016/j.uclim.2020.100610
- Detection of fossil fuel emission trends in the presence of natural carbon cycle variability Y. Yin et al. 10.1088/1748-9326/ab2dd7
- Lagrangian inversion of anthropogenic CO2 emissions from Beijing using differential column measurements K. Che et al. 10.1088/1748-9326/ac7477
- Comparison of OCO-2 target observations to MUCCnet – is it possible to capture urban XCO2 gradients from space? M. Rißmann et al. 10.5194/amt-15-6605-2022
- Assessing the Effectiveness of an Urban CO2 Monitoring Network over the Paris Region through the COVID-19 Lockdown Natural Experiment J. Lian et al. 10.1021/acs.est.1c04973
- Development of a regional carbon assimilation system and its application for estimating fossil fuel carbon emissions in the Yangtze River Delta, China Z. Zhang et al. 10.1016/j.scitotenv.2024.177720
- The first 1-year-long estimate of the Paris region fossil fuel CO<sub>2</sub> emissions based on atmospheric inversion J. Staufer et al. 10.5194/acp-16-14703-2016
- Characterization of a commercial lower-cost medium-precision non-dispersive infrared sensor for atmospheric CO<sub>2</sub> monitoring in urban areas E. Arzoumanian et al. 10.5194/amt-12-2665-2019
- Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties K. Wu et al. 10.1525/elementa.138
- Complementing XCO2 imagery with ground-based CO2 and 14CO2 measurements to monitor CO2 emissions from fossil fuels on a regional to local scale E. Potier et al. 10.5194/amt-15-5261-2022
- Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL S. Vardag & R. Maiwald 10.5194/gmd-17-1885-2024
- Bayesian Optimization of the Community Land Model Simulated Biosphere–Atmosphere Exchange using CO2 Observations from a Dense Tower Network and Aircraft Campaigns over Oregon A. Schmidt et al. 10.1175/EI-D-16-0011.1
- Carbon dioxide, methane and nitrous oxide emissions from the human-impacted Seine watershed in France A. Marescaux et al. 10.1016/j.scitotenv.2018.06.151
- Sustained Reductions of Bay Area CO2 Emissions 2018–2022 N. Asimow et al. 10.1021/acs.est.3c09642
- Development and deployment of a mid-cost CO2 sensor monitoring network to support atmospheric inverse modeling for quantifying urban CO2 emissions in Paris J. Lian et al. 10.5194/amt-17-5821-2024
- Designing additional CO2 in-situ surface observation networks over South Korea using bayesian inversion coupled with Lagrangian modelling S. Takele Kenea et al. 10.1016/j.atmosenv.2024.120471
- Estimates of CO<sub>2</sub> fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling A. Nickless et al. 10.5194/acp-18-4765-2018
- Estimates of Anthropogenic CO2 Emissions for Moscow and St. Petersburg Based on OCO-2 Satellite Measurements Y. Timofeev et al. 10.1134/S1024856020060238
- The BErkeley Atmospheric CO<sub>2</sub> Observation Network: initial evaluation A. Shusterman et al. 10.5194/acp-16-13449-2016
- Comparison of Global Downscaled Versus Bottom‐Up Fossil Fuel CO2 Emissions at the Urban Scale in Four U.S. Urban Areas K. Gurney et al. 10.1029/2018JD028859
- Evaluation of light atmospheric plume inversion methods using synthetic XCO2 satellite images to compute Paris CO2 emissions A. Danjou et al. 10.1016/j.rse.2023.113900
- Analysis of anthropogenic CO2 emission uncertainty and influencing factors at city scale in Yangtze River Delta region: One of the world's largest emission hotspots H. Liu et al. 10.1016/j.apr.2024.102281
- Optimal design of surface CO2 observation network to constrain China’s land carbon sink Y. Wang et al. 10.1016/j.scib.2023.07.010
- Site selection and effects of background towers on urban CO2 estimates: A case study from central downtown Zhengzhou in China G. Ren et al. 10.1016/j.envres.2024.120169
- A high-resolution monitoring approach of urban CO2 fluxes. Part 2 – surface flux optimisation using eddy covariance observations S. Stagakis et al. 10.1016/j.scitotenv.2023.166035
- Evaluation of Low-Cost CO2 Sensors Using Reference Instruments and Standard Gases for Indoor Use Q. Cai et al. 10.3390/s24092680
- Analysis of temporal and spatial variability of atmospheric CO<sub>2</sub> concentration within Paris from the GreenLITE™ laser imaging experiment J. Lian et al. 10.5194/acp-19-13809-2019
- Network design for quantifying urban CO<sub>2</sub> emissions: assessing trade-offs between precision and network density A. Turner et al. 10.5194/acp-16-13465-2016
- An atmospheric inversion over the city of Cape Town: sensitivity analyses A. Nickless et al. 10.5194/acp-19-7789-2019
- Can we use atmospheric CO2 measurements to verify emission trends reported by cities? Lessons from a 6-year atmospheric inversion over Paris J. Lian et al. 10.5194/acp-23-8823-2023
- Diagnostic methods for atmospheric inversions of long-lived greenhouse gases A. Michalak et al. 10.5194/acp-17-7405-2017
- Sensitivity to the sources of uncertainties in the modeling of atmospheric CO<sub>2</sub> concentration within and in the vicinity of Paris J. Lian et al. 10.5194/acp-21-10707-2021
- Analysis of total column CO<sub>2</sub> and CH<sub>4</sub> measurements in Berlin with WRF-GHG X. Zhao et al. 10.5194/acp-19-11279-2019
- Diurnal, synoptic and seasonal variability of atmospheric CO<sub>2</sub> in the Paris megacity area I. Xueref-Remy et al. 10.5194/acp-18-3335-2018
- A city-level comparison of fossil-fuel and industry processes-induced CO2 emissions over the Beijing-Tianjin-Hebei region from eight emission inventories P. Han et al. 10.1186/s13021-020-00163-2
- A Method for Estimating the Background Column Concentration of CO2 Using the Lagrangian Approach Z. Pei et al. 10.1109/TGRS.2022.3176134
Saved (preprint)
Discussed (final revised paper)
Latest update: 13 Dec 2024
Short summary
This paper advances atmospheric inversion of city CO2 emissions as follows: (1) illustrate how inversion methodology can be tailored to deal with very large urban networks of sensors measuring CO2 concentrations; (2) demonstrate that atmospheric inversion could be a relevant tool of Monitoring, Reporting and Verification (MRV) of city CO2 emissions; (3) clarify the theoretical potential of inversion for reducing uncertainties in the estimates of citywide total and sectoral CO2 emissions.
This paper advances atmospheric inversion of city CO2 emissions as follows: (1) illustrate how...
Altmetrics
Final-revised paper
Preprint