The problem of dust emissions from playa sources is an important one both in terms of human health and in terms of global dust issues, distribution of loess, and mineral cycling. A refined method of modeling atmospheric dust concentrations due to wind erosion was developed using real‐time saltation flux measurements and ambient dust monitoring data at Owens Lake, California. This modeling method may have practical applications for modeling the atmospheric effects of wind erosion in other areas. Windblown dust from the Owens Lake bed often causes violations of federal air quality standards for particulate matter (PM₁₀) that are the highest levels measured in the United States. The goal of this study was to locate dust source areas on the exposed lake bed, estimate their PM₁₀ emissions, and use air pollution modeling techniques to determine which areas caused or contributed to air quality violations. Previous research indicates that the vertical flux of PM₁₀ (F_a) is generally proportional to the total horizontal saltation flux (q) for a given soil texture and surface condition. For this study, hourly PM₁₀ emissions were estimated using F_a = K′ × m₁₅, where m₁₅ is the measured sand flux at 15 cm above the surface, and K′ was derived empirically by comparing air quality model predictions to monitored PM₁₀ concentrations. Hourly sand flux was measured at 135 sites (1 km spacing) on the lake bed, and PM₁₀ was monitored at six off‐lake sites for a 30 month period. K′ was found to change spatially and temporally over the sampling period. These changes appeared to be linked to different soil textures and to seasonal surface changes. K′ values compared favorably with other F_a/q values measured at Owens Lake using portable wind tunnel and micrometeorological methods. Hourly trends for the model‐predicted PM₁₀ concentrations agreed well with monitored PM₁₀ concentrations. Dust production was estimated at 7.2 × 10⁴ t of PM₁₀ for a 12 month period. A single storm accounted for 9% of the annual dust emissions at 6.5 × 10³ t. The modeling results were used to identify 77 km² of dust‐producing areas on the lake bed that will be controlled to attain the federal air quality standard for PM₁₀.