Monitoring CO emissions of the metropolis Mexico City using TROPOMI CO observations

The Tropospheric Monitoring Instrument (TROPOMI) on the ESA Copernicus Sentinel-5 satellite (S5-P) measures carbon monoxide (CO) total column concentrations as one of its primary targets. In this study, we analyze TROPOMI observations over Mexico City in the period 14 November 2017 to 25 August 2019...

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Published in:Atmospheric chemistry and physics 2020-12, Vol.20 (24), p.15761-15774
Main Authors: Borsdorff, Tobias, García Reynoso, Agustín, Maldonado, Gilberto, Mar-Morales, Bertha, Stremme, Wolfgang, Grutter, Michel, Landgraf, Jochen
Format: Article
Language:English
Subjects:
Air pollution
Algorithms
Analysis
Atmospheric chemistry
Atmospheric composition
Atmospheric models
Carbon monoxide
Carbon monoxide emissions
Data interpretation
Datasets
Emission inventories
Emissions
Exploitation
Fourier analysis
Fourier transform spectrometers
Fourier transforms
Ground-based observation
In situ measurement
Local winds
Meteorological research
Monitoring instruments
Noise propagation
Numerical weather forecasting
Pollution monitoring
Simulation
Temporal variability
Temporal variations
Tracers
Urban areas
Weather
Weather forecasting
Weekly
Wind fields
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container_issue 24
container_start_page 15761
container_title Atmospheric chemistry and physics
container_volume 20
creator Borsdorff, Tobias
García Reynoso, Agustín
Maldonado, Gilberto
Mar-Morales, Bertha
Stremme, Wolfgang
Grutter, Michel
Landgraf, Jochen
description The Tropospheric Monitoring Instrument (TROPOMI) on the ESA Copernicus Sentinel-5 satellite (S5-P) measures carbon monoxide (CO) total column concentrations as one of its primary targets. In this study, we analyze TROPOMI observations over Mexico City in the period 14 November 2017 to 25 August 2019 by means of collocated CO simulations using the regional Weather Research and Forecasting coupled with Chemistry (WRF-Chem) model. We draw conclusions on the emissions from different urban districts in the region. Our WRF-Chem simulation distinguishes CO emissions from the districts Tula, Pachuca, Tulancingo, Toluca, Cuernavaca, Cuautla, Tlaxcala, Puebla, Mexico City, and Mexico City Arena by 10 separate tracers. For the data interpretation, we apply a source inversion approach determining per district the mean emissions and the temporal variability, the latter regularized to reduce the propagation of the instrument noise and forward-model errors in the inversion. In this way, the TROPOMI observations are used to evaluate the Inventario Nacional de Emisiones de Contaminantes Criterio (INEM) inventory that was adapted to the period 2017–2019 using in situ ground-based observations. For the Tula and Pachuca urban areas in the north of Mexico City, we obtain 0.10±0.004 and 0.09±0.005 Tg yr−1 CO emissions, which exceeds significantly the INEM emissions of
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In this study, we analyze TROPOMI observations over Mexico City in the period 14 November 2017 to 25 August 2019 by means of collocated CO simulations using the regional Weather Research and Forecasting coupled with Chemistry (WRF-Chem) model. We draw conclusions on the emissions from different urban districts in the region. Our WRF-Chem simulation distinguishes CO emissions from the districts Tula, Pachuca, Tulancingo, Toluca, Cuernavaca, Cuautla, Tlaxcala, Puebla, Mexico City, and Mexico City Arena by 10 separate tracers. For the data interpretation, we apply a source inversion approach determining per district the mean emissions and the temporal variability, the latter regularized to reduce the propagation of the instrument noise and forward-model errors in the inversion. In this way, the TROPOMI observations are used to evaluate the Inventario Nacional de Emisiones de Contaminantes Criterio (INEM) inventory that was adapted to the period 2017–2019 using in situ ground-based observations. For the Tula and Pachuca urban areas in the north of Mexico City, we obtain 0.10±0.004 and 0.09±0.005 Tg yr−1 CO emissions, which exceeds significantly the INEM emissions of &lt;0.008 Tg yr−1 for both areas. On the other hand for Mexico City, TROPOMI estimates emissions of 0.14±0.006 Tg yr−1 CO, which is about half of the INEM emissions of 0.25 Tg yr−1, and for the adjacent district Mexico City Arena the emissions are 0.28±0.01 Tg yr−1 according to TROPOMI observations versus 0.14 Tg yr−1 as stated by the INEM inventory. Interestingly, the total emissions of both districts are similar (0.42±0.016 Tg yr−1 TROPOMI versus 0.39 Tg yr−1 adapted INEM emissions). Moreover, for both areas we found that the TROPOMI emission estimates follow a clear weekly cycle with a minimum during the weekend. This agrees well with ground-based in situ measurements from the Secretaría del Medio Ambiente (SEDEMA) and Fourier transform spectrometer column measurements in Mexico City that are operated by the Network for the Detection of Atmospheric Composition Change Infrared Working Group (NDACC-IRWG). Overall, our study demonstrates an approach to deploying the large number of TROPOMI CO data to draw conclusions on urban emissions on sub-city scales for metropolises like Mexico City. 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In this study, we analyze TROPOMI observations over Mexico City in the period 14 November 2017 to 25 August 2019 by means of collocated CO simulations using the regional Weather Research and Forecasting coupled with Chemistry (WRF-Chem) model. We draw conclusions on the emissions from different urban districts in the region. Our WRF-Chem simulation distinguishes CO emissions from the districts Tula, Pachuca, Tulancingo, Toluca, Cuernavaca, Cuautla, Tlaxcala, Puebla, Mexico City, and Mexico City Arena by 10 separate tracers. For the data interpretation, we apply a source inversion approach determining per district the mean emissions and the temporal variability, the latter regularized to reduce the propagation of the instrument noise and forward-model errors in the inversion. In this way, the TROPOMI observations are used to evaluate the Inventario Nacional de Emisiones de Contaminantes Criterio (INEM) inventory that was adapted to the period 2017–2019 using in situ ground-based observations. For the Tula and Pachuca urban areas in the north of Mexico City, we obtain 0.10±0.004 and 0.09±0.005 Tg yr−1 CO emissions, which exceeds significantly the INEM emissions of &lt;0.008 Tg yr−1 for both areas. On the other hand for Mexico City, TROPOMI estimates emissions of 0.14±0.006 Tg yr−1 CO, which is about half of the INEM emissions of 0.25 Tg yr−1, and for the adjacent district Mexico City Arena the emissions are 0.28±0.01 Tg yr−1 according to TROPOMI observations versus 0.14 Tg yr−1 as stated by the INEM inventory. Interestingly, the total emissions of both districts are similar (0.42±0.016 Tg yr−1 TROPOMI versus 0.39 Tg yr−1 adapted INEM emissions). Moreover, for both areas we found that the TROPOMI emission estimates follow a clear weekly cycle with a minimum during the weekend. This agrees well with ground-based in situ measurements from the Secretaría del Medio Ambiente (SEDEMA) and Fourier transform spectrometer column measurements in Mexico City that are operated by the Network for the Detection of Atmospheric Composition Change Infrared Working Group (NDACC-IRWG). Overall, our study demonstrates an approach to deploying the large number of TROPOMI CO data to draw conclusions on urban emissions on sub-city scales for metropolises like Mexico City. 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In this study, we analyze TROPOMI observations over Mexico City in the period 14 November 2017 to 25 August 2019 by means of collocated CO simulations using the regional Weather Research and Forecasting coupled with Chemistry (WRF-Chem) model. We draw conclusions on the emissions from different urban districts in the region. Our WRF-Chem simulation distinguishes CO emissions from the districts Tula, Pachuca, Tulancingo, Toluca, Cuernavaca, Cuautla, Tlaxcala, Puebla, Mexico City, and Mexico City Arena by 10 separate tracers. For the data interpretation, we apply a source inversion approach determining per district the mean emissions and the temporal variability, the latter regularized to reduce the propagation of the instrument noise and forward-model errors in the inversion. In this way, the TROPOMI observations are used to evaluate the Inventario Nacional de Emisiones de Contaminantes Criterio (INEM) inventory that was adapted to the period 2017–2019 using in situ ground-based observations. For the Tula and Pachuca urban areas in the north of Mexico City, we obtain 0.10±0.004 and 0.09±0.005 Tg yr−1 CO emissions, which exceeds significantly the INEM emissions of &lt;0.008 Tg yr−1 for both areas. On the other hand for Mexico City, TROPOMI estimates emissions of 0.14±0.006 Tg yr−1 CO, which is about half of the INEM emissions of 0.25 Tg yr−1, and for the adjacent district Mexico City Arena the emissions are 0.28±0.01 Tg yr−1 according to TROPOMI observations versus 0.14 Tg yr−1 as stated by the INEM inventory. Interestingly, the total emissions of both districts are similar (0.42±0.016 Tg yr−1 TROPOMI versus 0.39 Tg yr−1 adapted INEM emissions). Moreover, for both areas we found that the TROPOMI emission estimates follow a clear weekly cycle with a minimum during the weekend. This agrees well with ground-based in situ measurements from the Secretaría del Medio Ambiente (SEDEMA) and Fourier transform spectrometer column measurements in Mexico City that are operated by the Network for the Detection of Atmospheric Composition Change Infrared Working Group (NDACC-IRWG). Overall, our study demonstrates an approach to deploying the large number of TROPOMI CO data to draw conclusions on urban emissions on sub-city scales for metropolises like Mexico City. Moreover, for the exploitation of TROPOMI CO observations our analysis indicates the clear need for further improvements of regional models like WRF-Chem, in particular with respect to the prediction of the local wind fields.</abstract><cop>Katlenburg-Lindau</cop><pub>Copernicus GmbH</pub><doi>10.5194/acp-20-15761-2020</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-9800-5878</orcidid><orcidid>https://orcid.org/0000-0002-4421-0187</orcidid><orcidid>https://orcid.org/0000-0003-0791-3833</orcidid><orcidid>https://orcid.org/0000-0001-7718-9241</orcidid><oa>free_for_read</oa></addata></record>
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subjects Air pollution
Algorithms
Analysis
Atmospheric chemistry
Atmospheric composition
Atmospheric models
Carbon monoxide
Carbon monoxide emissions
Data interpretation
Datasets
Emission inventories
Emissions
Exploitation
Fourier analysis
Fourier transform spectrometers
Fourier transforms
Ground-based observation
In situ measurement
Local winds
Meteorological research
Monitoring instruments
Noise propagation
Numerical weather forecasting
Pollution monitoring
Simulation
Temporal variability
Temporal variations
Tracers
Urban areas
Weather
Weather forecasting
Weekly
Wind fields
title Monitoring CO emissions of the metropolis Mexico City using TROPOMI CO observations
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