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Data quality reporting: Good practice for transparent estimates from forest and land cover surveys

Author:
Birigazzi, Luca, Gregoire, Timothy G., Finegold, Yelena, Cóndor Golec, Rocío D., Sandker, Marieke, Donegan, Emily, Gamarra, Javier G.P.
Source:
Environmental science & policy 2019 v.96 pp. 85-94
ISSN:
1462-9011
Subject:
United Nations Framework Convention on Climate Change, confidence interval, data quality, emissions factor, environmental science, forest inventory, forests, greenhouse gas emissions, greenhouse gases, issues and policy, land cover, national forests, quality control
Abstract:
The need to provide transparent and reliable Greenhouse Gas (GHG) emission estimates is strongly emphasized in the context of international reporting under the United Nations Framework Convention on Climate Change (UNFCCC) and the Paris Agreement. Yet it is difficult to find specific guidance about what information is really needed to evaluate the quality of the emission factors or activity data used for GHG emission estimates. The most commonly used indicator of the reliability of an estimation procedure (and one of the few indicators explicitly mentioned in the 2006 IPCC guidelines) is the so-called confidence interval, usually at a confidence level of 90% or 95%. This interval, however, is unlikely to be a meaningful indicator of the quality of the estimate, if not associated with additional information about the estimation and survey procedures (such as on the sampling design, measurement protocols or quality control routines, among others). We provide a review of the main sources of error that can have an impact on the precision and accuracy of the estimation of both emission factors and activity data and a list of the essential survey features that should be reported to properly evaluate the quality of a GHG emission estimate. Such list is also applicable to the reporting of national forest inventories and of area estimation of activity data, and includes the case in which confidence intervals are obtained using error propagation techniques.
Agid:
6347634