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Factors affecting carbon dioxide anomalies

Thin soils underlain by limestone can also be the source of false anomalies. On a traverse across a molybdenum deposit at Tongsban, Jiangsu province, which is covered by 0.3-1.0 m of eluvium, CO2 anomalies were found not only above the ore body but also on a nearby ridge. Here soils are particularly thin and poorly developed, and the underlying limestone creates an environment in which the pH can be as high as 8.5, allowing carbonate enrichment which in turn produces a false anomaly of CO2. [Pg.131]

The natural organic carbon content of the soil can affect the amount of CO2 detected, and evidence from one traverse suggests that proximity to the exhaust residues of road traffic could also be a source of CO2 in soil. The ratio of CO2 to organic carbon can be used to resolve this problem. [Pg.131]

Carbon dioxide, probably introduced at the time of emplacement of mineralisation, occurs in a form that is easily released at 100°C as halo around and above many mineral deposits. Along soil traverses over nine mineral deposits in China, determination of this CO2 yields good-contrast anomalies, even when the mineralisation is deeply buried. There is also an elevated CO2 expression in soils over faults in mineralised areas. [Pg.131]

In general, over those mineral deposits in China where both methods have been tested, there is considerable agreement between CO2 patterns and thermally-released Hg patterns (Chapter 13). The continuity and intensity of CO2 anomalies tends to be a little poorer. On the other hand, in some cases CO2 anomalies are present over mineralisation where thermally-released Hg anomalies are absent. [Pg.131]

The recognition of CO2 anomalies in soils can be used, along with other methods, for the detection of buried and blind mineral deposits. Samples are easy to obtain and prepare, and the same samples can be used for other routine geochemical analyses. The method described here for the determination of CO2 is simple, efficient, inexpensive and can be used to analyse large numbers of samples. [Pg.132]


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