<p><strong>Abstract.</strong> In Colombia, industrialization and a shift towards intensified agriculture have led to increased emissions of air pollutants. However, the baseline state of air quality in Colombia is relatively unknown. In this study we aim to assess the baseline state of air quality in Colombia with a focus on the spatial and temporal variability in emissions and atmospheric burden of nitrogen oxides (NO<sub>x</sub>&#8201;=&#8201;NO&#8201;+&#8201;NO<sub>2</sub>) and evaluate surface NO<sub>x</sub>, ozone (O<sub>3</sub>) and carbon monoxide (CO) mixing ratios. We quantify the magnitude and spatial distribution of the four major NO<sub>x</sub> sources (lightning, anthropogenic activities, soil biogenic emissions and biomass burning), by integrating global NO<sub>x</sub> emission inventories into the mesoscale meteorology and atmospheric chemistry model WRF-Chem. The comparison with in situ measurements is bound to urban areas whereas the use of remote sensing data allows to also evaluate air quality in remote regions. WRF-Chem was set up for a domain centered over Colombia with a similar resolution as OMI observed NO<sub>2</sub> vertical columns as well as the EDGAR anthropogenic emission inventory, both providing information on a ~20&#8201;km resolution. However, this apparently poses a challenge regarding comparison with these urban observations. Air mass factors were recalculated based on the vertical distribution of NO<sub>2</sub> within WRF-Chem, with respect to the coarse (1&#176;&#8201;x&#8201;1&#176;) a priori profiles. The main reason for recalculation is a more consistent satellite-model comparison but it also reduced the mean bias. WRF-Chem was, on average, able to provide good estimates for tropospheric NO<sub>2</sub> columns with an averaged difference of 0.02&#8201;x&#8201;10<sup>15</sup>&#8201;molecules&#8201;cm<sup>-2</sup>, which is <&#8201;5&#8201;% of the mean column. However, the simulated NO<sub>2</sub> columns are overestimated in regions with abundant modeled lightning emissions and underestimated in regions where biomass burning emissions dominate in the model. This result reflects the high contribution by lightning emissions (1258&#8201;Gg&#8201;N&#8201;yr<sup>-1</sup>) and the low contribution by biomass burning emissions (104&#8201;Gg&#8201;N&#8201;yr<sup>-1</sup>) to total NO<sub>x</sub> emissions within the WRF-Chem domain. WRF-Chem was unable to capture NO<sub>x</sub> and CO urban pollutant mixing ratios, both in timing and magnitude. Yet, WRF-Chem was able to simulate the urban diurnal cycle of O<sub>3</sub> satisfactory but with a systematic overestimation of 10&#8201;ppb due to the equally large underestimation of NO mixing ratios and, consequently, titration. This indicates that these city environments are in the NO<sub>x</sub> saturated regime with frequent O<sub>3</sub> titration. We also applied an online meteorology-chemistry single column model (SCM) to evaluate how enhanced emissions and different representation of advection and mixing conditions could explain an improved representation of the observed O<sub>3</sub> and NO<sub>x</sub> diurnal cycles. The SCM appears to indeed better represent the observed diurnal cycle of urban pollutant mixing ratios. But, interestingly, this result did not require an enhancement in the emissions, indicating that the role of boundary layer dynamics and advection should be considered besides the use of high-resolution models and emissions inventories to realistically simulate urban air quality. Results obtained in this study provide insight in the magnitude, distribution and temporal evolution of different sources of pollution in Colombia and its surrounding territories. This study not only identifies different source regions, but also shows the interannual variability of these sources during the last one and a half decade using satellite data. Furthermore, this study shows that relatively coarse anthropogenic emission inventories can give reasonable results regarding the diurnal cycle of urban pollutant mixing ratios with a careful consideration of advection and mixing conditions. It serves as a base to assess scenarios of future air quality in Colombia, or similar regions with distinct contrasting emission regimes and a limited air quality monitoring network, as a function of further industrialization and land use changes.</p>