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ND, not determined. a All values in µg/kg/day based on a maximum creatinine clearance of 20 mg/kg/day. b Estimated intake taken from ATSDR, IPCS, or EU draft risk assessments. c From Doull et al. (4) using ATSDR estimates.

ND, not determined. a All values in µg/kg/day based on a maximum creatinine clearance of 20 mg/kg/day. b Estimated intake taken from ATSDR, IPCS, or EU draft risk assessments. c From Doull et al. (4) using ATSDR estimates.

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Diverse urban air pollution sources contribute to spatially variable atmospheric concentrations, with important public health implications. Mobile monitoring shows promise for understanding spatial pollutant patterns, yet it is unclear whether uncertainties associated with temporally sparse sampling and instrument performance limit our ability to identify locations of elevated pollution. To address this question, we analyze 9 months of repeated weekday daytime on-road mobile measurements of black carbon (BC), particle number (PN), and nitrogen oxide (NO, NO 2 ) concentrations within 24 census tracts across Houston, Texas. We quantify persistently elevated, intermittent, and extreme concentration behaviors at 50 m road segments on surface streets and 90 m segments on highways relative to median statistics across the entire sampling domain. We find elevated concentrations above uncertainty levels (±40%) within portions of every census tract, with median concentration increases ranging from 2 to 3× for NO 2 , and >9× for NO. In contrast, PN exhibits elevated concentrations of 1.5−2× the domainwide median and distinct spatial patterns relative to other pollutants. Co-located elevated concentrations of primary combustion tracers (BC and NO x ) near 30% of metal recycling and concrete batch plant facilities within our sampled census tracts are comparable to those measured within 200 m of highways. Our results demonstrate how extensive mobile monitoring across multiple census tracts can quantitatively characterize urban air pollution source patterns and are applicable to developing effective source mitigation policies.