Conventional approaches to air pollution monitoring are limited in many regions because of their high costs and the need for extensive sampling. Therefore, indirect approaches using biomonitors have attracted increasing attention as simple and cost-effective alternatives. In this study, leaves of Pinus eldarica were used as a potential biomonitor to assess heavy metal contamination in atmospheric dust and identify its potential sources in Kerman, southeastern Iran. The concentrations of iron (Fe), manganese (Mn), zinc (Zn), and copper (Cu) were determined in washed (WL) and unwashed (UL) leaves, and the concentrations of metals deposited as dust on the leaf surfaces were calculated from the difference between UL and WL concentrations. The results showed that the mean concentrations of metals in the deposited dust followed the order Fe > Mn > Zn > Cu. The concentrations of all investigated metals were also higher in high-traffic areas than in low-traffic areas. Spatial distribution patterns showed that Cu, Zn, and Fe exhibited similar patterns, whereas Mn displayed a distinct spatial distribution. Principal component analysis and cluster analysis further supported this separation, with Cu, Zn, and Fe generally grouped together, while Mn exhibited a different behavior, particularly in high-traffic areas. The highest concentrations of Fe, Zn, and Cu were mainly observed in the western part of the city, in the vicinity of the airport, railway, major roads, and industrial areas. Overall, the results indicated that metal contamination in urban dust in Kerman is influenced by both anthropogenic and natural sources. Traffic- and industrial-related sources likely play important roles in increasing Cu and Zn concentrations and, to some extent, Fe, whereas Mn showed a stronger association with natural and lithogenic sources. Accordingly, it is recommended that the monitoring and management of metal contamination in Kerman focus on high-traffic and industrial hotspots, particularly in the western part of the city, with priority given to controlling emissions from traffic and industrial activities in these areas. In addition, P. eldarica could be considered a simple and cost-effective tool for preliminary monitoring and identifying the spatial patterns of metal contamination in urban monitoring programs.