Diesel-powered vehicles are intensively used in urban areas for transporting goods and people but can substantially contribute to high emissions of black carbon (BC), organic carbon (OC), and other gaseous pollutants. Strategies aimed at controlling mobile emissions sources thus have the potential to improve air quality and help mitigate the impacts of air pollutants on climate, ecosystems, and human health. However, in developing countries there are limited data on the BC and OC emission characteristics of diesel-powered vehicles, and thus there are large uncertainties in the estimation of the emission contributions from these sources. We measured BC, OC, and other inorganic components of fine particulate matter (PM), as well as carbon monoxide (CO), nitrogen oxides (NO_x), sulfur dioxide (SO₂), ethane, acetylene, benzene, toluene, and C2-benzenes under real-world driving conditions for 20 diesel-powered vehicles encompassing multiple emission level technologies in Mexico City with the chasing technique using the Aerodyne mobile laboratory. Average BC emission factors ranged from 0.41–2.48 g kg⁻¹ of fuel depending on vehicle type. The vehicles were also simultaneously measured using the cross-road remote sensing technique to obtain the emission factors of nitrogen oxide (NO), CO, total hydrocarbons, and fine PM, thus allowing for the intercomparison of the results from the two techniques. There is overall good agreement between the two techniques and both can identify high and low emitters, but substantial differences were found in some of the vehicles, probably due to the ability of the chasing technique to capture a larger diversity of driving conditions in comparison to the remote sensing technique. A comparison of the results with the US EPA MOVES2014b model showed that the model underestimates CO, OC, and selected VOC species, whereas there is better agreement for NO_x and BC. Larger OC / BC ratios were found in comparison to ratios measured in California using the same technique, further demonstrating the need for using locally obtained diesel-powered vehicle emission factor database in developing countries in order to reduce the uncertainty in the emissions estimates and to improve the evaluation of the effectiveness of emissions reduction measures.