Our study is a preparatory exercise. We focus on the analysis of uncertainty in greenhouse gas emission inventories.

The uncertainty of reported greenhouse gases emission inventories obtained by the aggregation of partial emissions from all sources and estimated to date for several countries is very high in comparison with the countries' emissions limitation and reduction commitments under the Kyoto Protocol. Independent calculation of the estimates could confirm or question the undertainty estimates values obtained thus far. One of the aims of this paper is to propose statistical signal processing methods to enable calculation of the inventory variances. The annual reported emissions are used and temporal smoothness of the emissions curve is assumed. The methods considered are: a spline-function-smoothing procedure; a time-varying parameter model; and the geometric Brownian motion model. These are validated on historical observations of the CO 2 emissions from fossil fuel combustion. The estimates of variances obtained are in a similar range to those obtained from national inventories using TIER1 or TIER2. Additionally, some regularities in the observed curves were noticed.

Praca zgłos zo na do czasopisma Climatic Change.