To conduct proper simulations for ozone, PM2.5, and fire smoke, it is necessary to understand the species composition
and leaf mass for California flora. Yet, leaf mass quantification and plant species composition and dominance may
be the weaker links in the development of biogenic emissions estimates, both for plants in urban settings and for
emission inventories at a regional level. Of particular interest in this regard are California native oaks, because
of their high emission rates, large area extent, and large masses of foliage. For California airsheds, the development
of the GAP land cover database in principle offers plant species-specific data useful for BVOC emission inventories.
However, although GAP is arguably the most recent and comprehensive land cover database available, it has been
developed for other purposes, especially for identifying habitats of threatened plant or animal species, and thus
may lack the degree of quantification needed for biogenic emissions inventory development.
Moreover, the translation of land cover data such as GAP to emissions models is problematic because a dimension
of leaf mass must be added to the existing data, or a relationship must be derived between data from remote sensing
and foliar masses.
Through a ground-truth approach in a series of ARB-sponsored studies, our group has generated experimental data
with which to evaluate the GAP database and to test leaf mass and leaf area estimation methodologies for urban
trees, California native oaks, and plants in natural communities. Continuation of leaf mass assessments in conjunction
with evaluation and development of new
vegetation maps remains a critical task for the Air Resources Board. |