Lakes and streams in Class 1 wilderness areas in the western United States (U.S.) are at risk from atmospheric deposition of nitrogen (N) and sulfur (S), and protection of these resources is mandated under the Federal Clean Air Act and amendments.  Assessment of critical loads, which are the maximum exposure to pollution an area can receive without adverse effects on sensitive ecosystems, requires accurate deposition estimates.  However, deposition is difficult and expensive to measure in high-elevation wilderness, and spatial patterns in N and S deposition in these areas remain poorly quantified.  In this study, ion-exchange resin (IER) collectors were used to measure dissolved inorganic N (DIN) and S deposition during June 2006 – September 2007 at approximately 20 alpine/subalpine sites spanning the Continental Divide in Rocky Mountain National Park.  Results indicated good agreement between deposition estimated from IER collectors and commonly used wet+dry methods during summer, but poor agreement during winter.  Snowpack sampling was found to be a more accurate way of quantifying DIN and S deposition during winter.  Summer DIN deposition was significantly greater on the east side of the park than on the west side (25-50%; p≤0.03), consistent with transport of pollutants to the park from urban and agricultural areas to the east.  Sources of atmospheric nitrate (NO₃^-) were examined using N isotopes.  The average d¹⁵N of NO₃^- from IER collectors was 3.5‰ greater during winter than during summer (p<0.001), indicating a seasonal shift in the relative importance of regional NOx sources, such as coal combustion and vehicular sources of atmospheric NO₃^-.  There were no significant differences in d¹⁵N of NO₃^- between east and west sides of the park during summer or winter (p=0.83), indicating that the two areas may have similar sources of atmospheric NO₃^-.  Results from this study indicate that a combination of IER collectors and snowpack sampling can be used to characterize spatial variability in DIN and S deposition in high-elevation wilderness areas.  These data can improve our ability to model critical loads by filling gaps in geographic coverage of deposition monitoring/modeling programs and thus may enable policy makers to better protect sensitive natural resources in Class 1 Wilderness areas.