Coastal locations are highly influenced by input from freshwater river runoff, including sources of terrestrial carbon, which can be expected to modify the <sup>14</sup>C reservoir age, or <i>R (t)</i>, associated with marine water. In this Baltic Sea case study, pre-bomb museum collection mollusc shells of known calendar age, from 30 locations across a strategic salinity transect of the Baltic Sea, were analysed for <sup>14</sup>C, δ<sup>13</sup>C and δ<sup>18</sup>O. <i>R (t)</i> was calculated for all 30 locations. Seven locations, of which six are within close proximity of the coast, were found to have relatively higher <i>R (t)</i> values, indicative of hard-water effects. Whenever possible, the <i>Macoma</i> genus of mollusc was selected from the museum collections, in order to exclude species specific reservoir age effects as much as possible. When the <i>Macoma</i> samples are exclusively considered, and samples from hard-water locations excluded, a statistically significant correlation between <i>Macoma</i> <i>R (t)</i> and average salinity is found, indicating a two end-member linear mixing model between <sup>14</sup>C<sub>marine</sub> and <sup>14</sup>C<sub>runoff</sub>. A map of Baltic Sea <i>Macoma</i> aragonite <i>R (t)</i> for the late 19th and early 20th centuries is produced. Such a map can provide an estimate for contemporary Baltic Sea <i>Macoma</i> <i>R (t)</i>, although one must exercise caution when applying such estimates back in time or to <sup>14</sup>C dates obtained from different sample material. A statistically significant correlation is found between δ<sup>18</sup>O<sub>aragonite</sub> and <i>Macoma</i> <i>R (t)</i>, suggesting that δ<sup>18</sup>O<sub>aragonite</sub> can be used to estimate <i>Macoma</i> palaeo-<i>R (t)</i>, due to the δ<sup>18</sup>O<sub>aragonite</sub> signal being dominated by the salinity gradient of the Baltic Sea. A slightly increased correlation can be expected when δ<sup>18</sup>O<sub>aragonite</sub> is corrected for temperature fractionation effects. The results of this Baltic Sea case study, which show that <i>R (t)</i> is affected by hydrographic conditions and local carbon inputs, have important consequences for other coastal and estuarine locations, where <i>R (t)</i> is also likely to significantly vary on spatial and temporal bases.