Abstract. Heavy metals are known to be among the one of the major environmental pollutants especially in urban areas and, as is generally known, can pose environmental risks as well as direct risks to humans. This study deals with the spatial distribution of heavy metals in different pavement joints in the inner-city area of Marburg (Hesse, Germany). Pavement joints, defined as the joint between paving stones and filled with different materials, have so far hardly been considered as anthropogenic urban soils. Nevertheless, they have an important role as possible sites of infiltration for surface runoff accumulation areas, and are therefore a key feature of urban water regimes. In order to investigate the spatial variability of heavy metals in pavement joints, a geospatial sampling approach was carried out on six inner-city sampling sites, followed by heavy metals analyses via ICP-MS, and additional pH and organic matter analyses. To obtain a risk assessment of heavy metal pollution, different pollution indices were calculated based on regional geochemical background values. Pavement joints examined consist mainly of basaltic gravel, sands, organic material and anthropogenic artefacts (e.g., glass, plastics) with an average joint size of 0.89 cm and a vertical depth of 2–10 cm. In general, the pavement joint material shows high organic matter loads (average 11.0 % by mass) and neutral to alkaline pH values. Besides high Al and Fe content, the heavy metals Cr, Ni, Cd and Pb are mainly responsible for the contamination of pavement joints. From the Geo-accumulation Index, the pollution in pavement joints regarding those metals, can be considered as moderate to high. Deterioration of soil quality was reported according to the Pollution Load Index (PLI) for 82.8 % of all sampling points, as well as a very strong potential Ecological Risk (RI) for 27.6 % of the points. The identified spatial pattern of maximum heavy metal loads in pavement joints, could not be attributed solely to traffic emissions, as commonly reported for urban areas. Higher concentrations were detected at runoff accumulation areas (e.g., drainage gutters), and at the lowest sampling points with high drainage accumulation tendencies. Additional Spearman correlation analyses show clear positive correlation between runoff accumulation value and PLI or RI index (rsp = 0.83; p