Governmental climate change mitigation targets are typically developed with the aid of forecasts of greenhouse-gas (GHG) emissions. The robustness and credibility of such forecasts depends, among other issues, on the extent to which forecasting approaches can reflect prevailing uncertainties. We apply a transparent and replicable method to quantify the uncertainty associated with projections of gross domestic product growth rates for Mexico, a key driver of GHG emissions in the country. We use those projections to produce probabilistic forecasts of GHG emissions for Mexico. We contrast our probabilistic forecasts with Mexico’s governmental deterministic forecasts. We show that, because they fail to reflect such key uncertainty, deterministic forecasts are ill-suited for use in target-setting processes. We argue that (i) guidelines should be agreed upon, to ensure that governmental forecasts meet certain minimum transparency and quality standards, and (ii) governments should be held accountable for the appropriateness of the forecasting approach applied to prepare governmental forecasts, especially when those forecasts are used to derive climate change mitigation targets.
POLICY INSIGHTS
No minimum transparency and quality standards exist to guide the development of GHG emission scenario forecasts, not even when these forecasts are used to set national climate change mitigation targets.
No accountability mechanisms appear to be in place at the national level to ensure that national governments rely on scientifically sound processes to develop GHG emission scenarios.
Using probabilistic forecasts to underpin emission reduction targets represents a scientifically sound option for reflecting in the target the uncertainty to which those forecasts are subject, thus increasing the validity of the target.
Setting up minimum transparency and quality standards, and holding governments accountable for their choice of forecasting methods could lead to more robust emission reduction targets nationally and, by extension, internationally.
GEOEXPLORER is a knowledge-based system under development to support the prospecting and exploration of supergene deposits. As a new type of multi-stage expert systetn, GEOEXPLORER is not only able to deal with problems of searching for supergene deposits, but will also cover both the evaluation of the spatial occurrences and the economic values of the deposits considered. A first prototype of GEOEXPLORER has been developed for bauxite deposits. It is a rule-based system implemented in PROLOG and can be used to identify favorable areas for bauxite prospecting. This paper discusses this prototype of GEOEXPLORER. 相似文献
Polycyclic aromatic hydrocarbons (PAHs) pollution, particularly in coastal environments, is a global concern. In this study, the biomonitoring and ranking effects of PAHs in the rockfish Sebastiscus marmoratus were determined in the Maowei Sea, China. The results showed that the concentrations of the 16 priority PAHs detected in the surface seawater were moderate compared with those in other coastal areas worldwide, and the possible sources were rapid industrialization and urbanization combined with atmospheric deposition and runoff. Nested analysis of variance (ANOVA) suggested significant differences in the hepatic ethoxyresorufin-O-deethylase (EROD) activities and phenanthrene-derived metabolites in bile between the port area and the oyster farming area. The fish expert system (FES) was applied to evaluate the biological effects of PAHs on fish. The FES data demonstrated that the biological effect levels of Site S1 (level III, medium stress) were higher than those of the other sampling sites (level II, low stress). 相似文献