Thermoluminescence dating tests for lacustrine, glaciomarine, and floodplain sediments from western Washington and British Columbia

To help further develop reliable procedures for accurate thermoluminescence (TL) dating of Quaternary waterlaid sediments, we tested TL dating procedures on sediment types rarely examined: six glaciolacustrine samples, three samples of glaciomarine drift, and eight samples of floodplain deposits. We used the partial-bleach (R-beta/gamma) technique applied to fine-silt polymineral grains. Results from our younger known-age glaciolacustrine sediments confirm earlier observations that only the clayey laminae are generally suitable for TL dating. A clayey lamina older than ca. 140 – 150 ka produced no age underestimation, and this result (ca. 300 ka) suggests that such older lake sediments are probably suitable for TL dating. Two proximal samples of glaciomarine drift produced large TL age overestimates, whereas the single distal glaciomarine-drift sample yielded an expected age (177 ± 38 ka), suggesting that follow-up studies are warranted. Our results for eight flood-plain samples confirm that zeroing of light-sensitive TL is more likely to be effective for sediments deposited in quiet, ponded water on the floodplain than for proximal sediments deposited from turbid floodwater. TL age estimates for floodplain sediments of the regional Whidbey Formation are consistent with its expected last-interglacial age, and those for two samples from stratigraphically older beds are consistent with deposition near or beyond 200 ka. Two of our younger samples (one lacustrine and one floodplain) gave TL age underestimates, perhaps because of use of ultraviolet TL emissions for these samples.

Multi-factor designs. IV. How multi-factor designs improve the estimate of total error by accounting for protocol-specific biases

Total error is often calculated as a combination of random error and fixed bias. However, the specific protocols used to estimate random error and fixed bias are themselves variable factors that can affect the estimate of total error. We refer to biases such as assay drift, sample-to-sample carryover, and reagent carryover as examples of fixed biases that are protocol-specific and distinguish them from other fixed biases. Failing to account for protocol-specific biases that are present will lead to incorrect estimates of total error when routine use of the assay involves a protocol different from that used to estimate total error. Multi-factor protocols are recommended to determine protocol-specific biases, which, if present, should be included in the estimate of total error.