Deposition of gaseous reactive nitrogen to forests and other ecosystems in the San Bernardino Mountains, California

Background/Question/Methods

Air pollution generated in the Los Angeles Basin affects forests and other ecosystems of the San Bernardino Mountains (SBM).  In addition to toxic effects of ozone, elevated levels of reactive nitrogen (N) lead to increased N deposition that result in exceedances of critical loads for nutritional N and negative effects on vegetation, soils and water. Until now estimates of N deposition in the SBM have been made using throughfall analyses.  However, because spatial coverage of throughfall estimates is poor and information on N deposition from CMAQ model is available only for selected years and requires additional testing, there is a need for an alternative methodology. We have applied the modified inferential method to determine N deposition in the SBM during summer seasons 2002 – 2006 using: (1) information on concentrations of main drivers of reactive N deposition (NH₃, HNO₃ and NO₂) obtained from passive samplers network; (2) empirical and modeled deposition velocities of these pollutants; (3) information on LAI from MODIS satellite images; and (4) land use classification of the Society of American Foresters and the Society for Range Management. A GIS platform was used to organize and generate results, and to produce distribution maps.

Results/Conclusions

There is a very strong gradient of HNO₃, NH₃ and NO₂ concentrations in the SBM with concentrations up to 17.5, 18.5 and ~30 ug m^-3 as 2-week averages, respectively.  Preliminary results also show a very strong W-E gradient of HNO₃ surface deposition and stomatal uptake resulting in NO₃^- deposition up to180 g N ha^-1 day^-1.  Similar steep gradients have been observed for gaseous reactive N, surface deposition of NH₄⁺ as well as NH₃ and NO₂ stomatal uptake resulting in high N deposition of serious ecological consequences. Our results will be compared with those obtained with methodology that uses improved dry deposition parameterization scheme (Zhang et al., 2003).