Every year, over 364,200 people in Europe die prematurely due to the effects of air pollution, in which the transportation sector plays an important role. In Brussels, freight transport generates €61,604 of air pollution health costs daily. Research has shown that dynamic spatiotemporal modeling of both emission sources and exposed people (using mobile phone data) renders more accurate impact results when analyzed in microenvi- ronments. However, mobile data underrepresent population segments that are more sensitive to the effects of air pollution, such as toddlers, children and elderly individuals. This paper examined the link between vulnerable people aged 0–3, 3–18 and >65 years and freight transport-related air pollution concentrations in the Brussels- Capital Region (BCR). To this end, dynamic tailpipe emissions and their spatiotemporal dispersion were calcu- lated using output from the Transport Agent-Based Model (TRABAM) on a daily basis. Population densities were calculated as a function of the residences’ occupancy rate and school/class size and opening hours. The effects of exposure were then evaluated using age- and sex-differentiated exposure-response functions and monetized using local hospital cost factors. Data were compiled for 2021. A strong overlap between people’s presence at the institutions’ locations was noticed with a peak in (freight) transportation movements in the city. The results showed that €37,000 [€34,517.47–€40,047.13] of freight transport-related air pollution health costs were incurred daily by vulnerable population segments. While these vulnerable groups made up 25.34% of the total BCR population, they incurred 60% [56.03%–65.01%] of the engendered transportation air pollution costs. The results were then geographically analyzed to identify 465 traffic-related air pollution hotspots across the terri- tory, which accounted for €36,000 [€33,677.85–€39,101.31] of total costs. The latter can be used in future studies to assess sector-specific freight transportation policies, which should take into consideration spatio- temporal population densities on the local level.