Abstract. 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 <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.

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Palabras clave: contaminación atmosférica, emisiones, distribución horaria, distribución geográfica, distribución especies químicas RESUMEN Este trabajo presenta el modelo de distribución espacial, temporal y de especiación (DiETE) del Inventario de Emisiones de México para el año base 2008. Se describen tanto la metodología utilizada como la información empleada para realizar la distribución espacial, temporal y química de las emisiones. Se muestran los resultados de la aplicación de este modelo al Inventario Nacional de Emisiones de México (INEM) 2008 y la validación del procedimiento. El INEM 2008 considera siete contaminantes (compuestos orgánicos volátiles [COV], amoniaco [NH3], óxido de nitrógeno [NOx], dióxido de azufre [SO2], monóxido de carbono [CO], y partículas PM10 y PM2.5) emitidos por tres tipos de fuentes: fijas, de área y móviles, las cuales se subdividen en 258, 64 y 17 categorías, respectivamente. A cada categoría se le relacionó con un código de clasificación de fuente (SCC, por sus siglas en inglés). Los perfiles de tiempo y especiación química se obtuvieron a partir del SCC de cada categoría. Se identificó que la masa total de los COV obtenidos con este modelo es hasta 17 % menor que el valor del inventario. El DiETE puede generar archivos para los mecanismos RADM2, RACM, CBM5 y SAPRC99, que emplea el model WRF-chem. Si bien se han utilizado modelos de emisiones en otros estudios, éste es el primero que incluye la validación en el procedimiento de conversión. Es útil para todo el año y se puede emplear para la evaluación de medidas mediante la modelización en la gestión ambiental.

Abstract. The Tropospheric Monitoring Instrument (TROPOMI) on ESA Copernicus Sentinel-5 satellite (S5-P) measures the carbon monoxide (CO) total column concentration as one of its primary targets. In this study, we analyse 551 TROPOMI overpasses over Mexico City (more than 2 years of measurements) using collocated CO simulations of the regional Weather Research and Forecasting (WRF) model to conclude on the emissions from different urban districts in the region. The WRF simulation distinguishes the CO emissions from Tula, Pachuca, Tulancingo, Toluca, Cuernavaca, Cuautla, Tlaxcala, Puebla, the metropolian area of Mexico City (CDMX), and the adjoint urban area (ACDMX, CDMX surrounding municipalities from estate of Mexico) by 10 separate tracers. Using a regularised source inversion approach, the TROPOMI observations yields 0.10 Tg/yr and 0.08 Tg/yr CO emissions from the Tula and Pachuca urban areas in the North of Mexico city. This exceeds significantly the Inventario Nacional de Emisiones de Contaminantes Criterio (INEM) inventory that was adapted to the period 2017–2019 and results in an emissions

In this work, we report the economic impact of exposure to high ozone concentrations on four important crops in the area of influence of the Mexico City Megalopolis. Estimated yield losses were as follows: maize: 3%; oats: 26%; beans: 14%; sorghum: 15%. The information needed to estimate the impact of air pollution in Mexico is decidedly deficient. Regarding ozone, the coverage provided by the monitoring networks is strongly focused on urban monitoring and its consistency over time is highly irregular. Apart from the Mexico City Metropolitan Area (MCMA) and less than a handful of other cities, the quality of the data is poor. Ozone in rural areas can be estimated with air quality models. However, these models depend on a high-resolution emissions inventory, which has only been done through validation processes in the MCMA. With these limitations, we set out to estimate the economic impact of exposure to ozone in these crops with a varying degree of sensitivity to ozone in the city belt of Central Mexico. To this end, we developed a procedure that makes optimal use of the sparse information available for construction of AOT40 (accumulated exposure over the threshold of 40 ppb) exceedance maps for the 2011 growing season. We believe that, due to the way in which we dealt with the sparse information and the uncertainty regarding the available data, our findings lie on the safe side of having little knowledge such that they may be useful to decision-makers. We believe that this procedure can be extended to the rest of the country, and that it may be useful to developing countries with similar monitoring and modeling capacities. In addition, these impacts are not evenly distributed in the region and sometimes they were greater in municipalities that have a higher index of poverty. Air pollution arriving from urban areas increases the social inequalities to which these already vulnerable populations are exposed.