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Comparison of methods for estimating carbon in harvested wood products

Authors :
Ana Cláudia Dias
Isabel Capela
Luís Arroja
Margarida Louro
Source :
Biomass and Bioenergy. 33:213-222
Publication Year :
2009
Publisher :
Elsevier BV, 2009.

Abstract

There is a great diversity of methods for estimating carbon storage in harvested wood products (HWP) and, therefore, it is extremely important to agree internationally on the methods to be used in national greenhouse gas inventories. This study compares three methods for estimating carbon accumulation in HWP: the method suggested by Winjum et al. (Winjum method), the tier 2 method proposed by the IPCC Good Practice Guidance for Land Use, Land-Use Change and Forestry (GPG LULUCF) (GPG tier 2 method) and a method consistent with GPG LULUCF tier 3 methods (GPG tier 3 method). Carbon accumulation in HWP was estimated for Portugal under three accounting approaches: stock-change, production and atmospheric-flow. The uncertainty in the estimates was also evaluated using Monte Carlo simulation. The estimates of carbon accumulation in HWP obtained with the Winjum method differed substantially from the estimates obtained with the other methods, because this method tends to overestimate carbon accumulation with the stock-change and the production approaches and tends to underestimate carbon accumulation with the atmospheric-flow approach. The estimates of carbon accumulation provided by the GPG methods were similar, but the GPG tier 3 method reported the lowest uncertainties. For the GPG methods, the atmospheric-flow approach produced the largest estimates of carbon accumulation, followed by the production approach and the stock-change approach, by this order. A sensitivity analysis showed that using the “best” available data on production and trade of HWP produces larger estimates of carbon accumulation than using data from the Food and Agriculture Organization.

Details

ISSN :
09619534
Volume :
33
Database :
OpenAIRE
Journal :
Biomass and Bioenergy
Accession number :
edsair.doi...........fdce6694c5ed9ca6b5c132719c77ef30