Comparison of Methods for Estimating Carbon Dioxide Storage by Sacramento’s Urban Forest

Abstract

Given the increasing demand for carbon dioxide storage estimates in urban areas and the high cost for ground-based inventories, there is need for more efficient approaches. Limited open-grown urban tree species biomass equations have necessitated use of forest-derived equations with diverse conclusions on the accuracy of these equations to estimate urban biomass and carbon storage. Our goal was to determine and explain variability among estimates of CO₂ storage from four sets of allometric equations for the same ground sample of 640 trees. Also, we compare the variability found in CO₂ stored and sequestered per hectare among estimation approaches for Sacramento’s urban forest with the variation found among six other cities. We found substantial variability among the four approaches. Storage estimates differed by a maximum of 29% and ranged from 38 to 49 t/ha. The two sequestration estimates differed by 55%, ranging from 1.8 to 2.8 t/ha. To put these numbers in perspective, they amounted to about one-tenth and one-quarter of the maximum differences in CO₂ storage and sequestration rates among six cities, respectively. i-Tree Eco produced the lowest storage estimates, perhaps because it relied exclusively on forest-based equations and applied a 0.80 correction factor to open-grown trees. The storage estimates produced by i-Tree Streets and CUFR Tree Carbon Calculator (CTCC) were the highest, while Urban General Equations produced relatively low estimates of CO₂ storage. Eco produced lower estimates of CO₂ sequestration rates than the CTCC across a range of species. Eco’s reductions for tree condition and projected mortality may partially explain the difference. An analysis of the roles of tree growth modeling and biomass equation selection for a green ash tree illustrated how the dynamic interaction between tree growth and biomass storage rate can influence the temporal stream of sequestration in complex ways. Based on these results we conclude that applying UGEs to remotely sensed data that accurately classify broadleaf, conifer and palm tree types in the Sacramento region is likely to produce conservative results compared to results from urban-based species-specific equations. The robustness of this result needs to be tested with different tree populations, and research is needed to establish relations between remotely-sensed tree crown projection area and dbh values required for biomass calculation. Of course, ground-based inventories remain necessary for more accurate estimates of CO₂ storage and for municipal forest management and health monitoring purposes.