The effects of sampling artifacts on cosmic dust flux estimates: a reevaluation of nonvolatile tracers (Os, Ir)

Geochimica et Cosmochimica Acta, Vol. 64, No. 11, pp. 1965–1970, 2000 Copyright © 2000 Elsevier Science Ltd Printed in the USA. All rights reserved 0016-7037/00 $20.00 ⫹ .00

Pergamon

PII S00167037(99)00429-9

The effects of sampling artifacts on cosmic dust flux estimates: A reevaluation of nonvolatile tracers (Os, Ir) BERNHARD PEUCKER-EHRENBRINK* and GREG RAVIZZA Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02543-1541 USA (Received July 27, 1999; accepted in revised form November 19, 1999)

Abstract—We reevaluate the effects of sampling artifacts on estimates of the flux of cosmic dust to Earth by modeling the population of extraterrestrial particles as a function of surface–area and time–interval sampled. Results from a Monte Carlo simulation for nonvolatile tracers such as Os and Ir indicate that samples corresponding to ⱖ2.5 m2a adequately sample the incoming extraterrestrial particle population. This applies to nearly all extraterrestrial flux estimates based on Os isotope data for marine sediments. New and revised flux estimates based on Os isotopes in marine sediments constrain the flux of extraterrestrial matter to the sea floor to 30,000 ⫾ 15,000 metric tons per year, within error identical to estimates of the flux of extraterrestrial matter to the top of Earth’s atmosphere. Care must be taken in the interpretation of iridium data for ice and snow samples because such samples are often too small to adequately sample the extraterrestrial particle population. The effects of systematic bias include large scatter in the data and underestimating the extraterrestrial matter flux. Copyright © 2000 Elsevier Science Ltd increases with decreasing particle diameter (e.g., Gru¨n et al., 1985; Love and Brownlee, 1993). However, the overall contribution to the mass of ET matter delivered to Earth decreases significantly to both sides of the peak in the mass spectrum. Therefore, attempts to quantify the annual accretion of ET partices on Earth have to ensure that large enough surface areas are sampled for sufficiently long time intervals to accurately sample particles defining the peak in the ET particle mass spectrum. The probability of missing large but rare ET particles increases with decreasing sample mass (i.e., decreasing area– time products, in units of m2a). This results in undersampling the ET particle population and, consequently, underestimating the accretion rates of ET matter. To model the effects of area–time products of sediment and ice/snow samples (sample weight divided by mass accumulation rate) on the accuracy and precision of estimates of ET matter flux to Earth we follow the approach of Farley et al. (1997) and use a Monte Carlo procedure with Poissonian distribution of the number of ET particles per ET particle size class. An implicit assumption in the use of the area–time product to evaluate sampling bias is that the stochastic nature of ET particle influx is analogous in space and time (i.e., a 10 m2 trap exposed for 1 yr is equivalent to a core sample with 10 cm2 surface area, which integrates 1000 yr). This assumption is valid only if the flux of ET particles is constant on a temporal and spatial scale representative for individual samples. Although there is no evidence for spatial variations in the flux of ET particles on the scale of individual samples, the existence of temporal variations in the flux over time scales corresponding to typical pelagic sediment samples (Farley and Patterson, 1995; Marcantonio et al., 1995, 1996) and even ice samples (Kayser et al., 1998) is currently being debated. The statistical basis for the model is the examination of hypervelocity impact craters on the space-facing end of the LDEF satellite (Love and Brownlee, 1993). For that study 761 craters on “thermal control panel” surfaces corresponding to ⬇32 m2a were analyzed. The population of large craters representing ET particles of ⱖ130 ␮m (thus including the peak in

1. INTRODUCTION

Results from statistical modeling of the extraterrestrial (ET) particle population (Farley et al., 1997) indicate that published flux estimates based on Os isotope data on marine sediments (Esser and Turekian, 1988, 1993; Ravizza and McMurtry, 1993; Peucker-Ehrenbrink, 1996) should be corrected upward by two to three orders of magnitude. If correct this would result in a large discrepancy between estimates of the ET matter flux to the seafloor and that to the top of the atmosphere (e.g., Love and Brownlee, 1993). A two- to three-order of magnitude higher ET matter flux would also have important implications for the interpretation of the marine Os isotope record, because dissolution of only a very small fraction of ET matter in seawater would balance radiogenic continental runoff without the need to invoke an unradiogenic, mantle-derived flux of Os to the oceans. This motivated us to reevaluate the effects of sampling artifacts on ET matter flux estimates. Using a very similar approach to that of Farley et al. (1997) we demonstrate below that new and published estimates of the ET matter flux based on Os isotope data are not biased by sampling artifacts and do not require a two- to three-order of magnitude correction. A reevaluation of the original model (Farley et al., 1997) for nonvolatile tracers revealed an error in the computations that led to the discrepancies outlined above. New calculations led to approximate reproduction of our model results presented below (K. Farley, personal communication, 1999). 2. THE MODEL

The mass distribution of small ET particles entering the Earth’s atmosphere is characterized by a strong peak at particle diameters of ⬇150 ␮m (for linear mass/size bins) and 220 ␮m (for log mass/size bins). The number of particles on the flanks of this peak decreases with increasing particle diameter and *Author to whom correspondence ([email protected]).

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the ET particle mass spectrum) was determined from 57 craters on panels H14 –H18 and H20 –H24, equivalent to ⬇19.6 m2a, as well as 55 craters on panels H13, H19, and H25, representing ⬇12.7 m2a. On the basis of these data Love and Brownlee (1993) estimate an annual cosmic dust flux of ⬇30,000 metric tons (40,000 ⫾ 20,000 metric tons to account for all cosmic dust). If this estimate is correct, area–time products of ⬇32 m2a are sufficient to accurately estimate the ET matter flux. Atmospheric entry heating leads to a shift in the size distribution to significantly smaller particle sizes caused by melting and vaporization of material (e.g., Love and Brownlee, 1991). With their atmospheric heating model Love and Brownlee (1991) show that typical melted ET particles experience reduction in size by a factor of 1.5–2 and reduction in mass by a factor of 3–10. This effect has profound effects on volatile tracers such as He, as outlined by Farley et al. (1997). The effects of atmospheric entry heating on nonvolatile tracers, however, are fundamentally different. Provided Platinum Group Elements (PGE) are not lost due to vaporization, reduction in particle size will lead to superchondritic concentrations of PGE, often associated with metallic Ni–Fe nuclei or platinum group element nuggets in micrometeorites (Brownlee et al., 1984). Analyses of individual 100 to 400 ␮m-sized micrometeorites reveal no difference in Os/Ir between unmelted (average Os/Ir ⫽ 0.96), metamorphosed (average Os/Ir ⫽ 0.96), and melted (average Os/Ir ⫽ 0.95) ET particles (Kurat et al., 1994). This is consistent with chondritic Os/Ir in individual platinum group nuggets (Brownlee et al., 1984). We argue that the lack of evidence for Os/Ir fractionation during atmospheric entry heating enables us to use the ET particle size distribution determined in space for modeling sampling artifact on Earth. This is a valid assumption as long as the reduction in particle size due to vaporization is accompanied by an increase in PGE concentration in the residual particle. However, the assumption is no longer valid if individual ET particles break up to form multiple smaller particles during entry heating or suffer vaporization of PGE followed by recondensation on small atmospheric particles below the altitude of maximum heating. We return to the implications of such a process for sampling biases associated with ice and snow samples at the end of the discussion. In the following section we use the polynomial fit to the cumulative crater density as a function of ET particle diameter (Fig. 1 in Love and Brownlee, 1993) and the algorithm for converting the crater size–frequency distribution to ET particle mass distribution (Eqn. 1 in Love and Brownlee, 1993) to calculate the number of ET particles in 19 linear bins covering the size range from 1 to 1000 ␮m. We then calculate the number of particles in each bin (i.e., size class) for a range of area–time products covering six orders of magnitude (0.00025– 250 m2a). The number of ET particles in each bin was simulated 2500 times using a Monte Carlo method with Poissonian distribution about the global mean value of the number of particles in each bin for a given area–time product. The number of ET particles per bin was translated into mass assuming spherical geometry of ET particles with an average density of 2.5 g/cm3 for melted and unmelted ET particles, and the mass of all ET particles for the given area–time product was computed by summing over all size classes. Finally the global mass was calculated as a product of this sum with the Earth’s surface

area divided by the area–time product used in the respective model. It is important to point out that the choice of binning (linear units versus log units, number of bins for a given size/mass interval) does not significantly affect the model results. Test with different bin sizes (i.e., number of total bins for the interval from 1 to 1000 ␮m) yield very similar, although not identical results. As these differences are not central to our arguments, they are not discussed further. 3. RESULTS AND DISCUSSION

The model results for seven area–time products spanning a wide range of values characteristic of snow, ice, and marine sediment samples are shown in Figure 1. These results significantly differ from those reported by Farley et al. (1997) and show that undersampling the ET matter flux using mass-related tracers such as Os and Ir in ice and marine sediments becomes significant only at area–time products of ⬍2.5 m2a. A unique feature of the frequency spectra is the quantized distribution pattern resulting from severe undersampling (i.e., very small number of particles per bin), shown here in Figure 2 for an area–time product of 0.00025 m2a. This area–time product is equivalent to a 4-min sampling period for the thermal control panels of the LDEF facility used by Love and Brownlee (1993). The majority of multiple 4 min integration periods will not collect any ET particles (i.e., zero normalized ET matter flux in Figure 2), whereas rare large ET particles captured sporadically during such short integration periods will yield normalized global ET matter flux Ⰷ1. The quantized distribution pattern is thus a consequence of extrapolating small area–time products (and thus small number of particles) to global flux values. Several conclusions can be drawn from the model results presented above. Most important, nonvolatile tracers of ET matter such as Ir and Os are valid tracers for estimating the global ET matter flux if sample masses correspond to area–time products of ⱖ2.5 m2a. In this context it should be noted that Os is a more sensitive tracer of ET matter than Ir because the large isotopic contrast between ET matter and continental detritus enables us to distinguish between those two end-members (see, for details Turekian, 1982; Esser and Turekian, 1988, 1993; Ravizza and McMurtry, 1993; Peucker-Ehrenbrink, 1996; Schmitz et al., 1997). In contrast, studies using Ir as a tracer for ET matter assume that either all (Tuncel and Zoller, 1987; Rocchia et al., 1990; Rasmussen et al., 1995) or a fraction of the Ir (Barker and Anders, 1968; Kyte and Wasson, 1986; Peucker-Ehrenbrink, 1996) is of ET origin. Quantifying the non-ET fraction of Ir is impossible with Ir data alone, and other tracers such as Os isotopes or circumstantial evidence such as trace element ratios have to be used. In the following (1) we present new Os isotope data from a pelagic sediment core (10400) from the NE Atlantic west of the Cape Verde Abyssal Plains; (2) estimate the ET matter flux using previously published Os isotope data for metalliferous sediments from the SW Pacific (DSDP 597 and 598; Reusch et al., 1998); and (3) reevaluate published ET flux estimates (Peucker-Ehrenbrink, 1996) with respect to potential sampling artifacts. 4. CONSTRAINTS FROM OS ISOTOPE DATA

New estimates of the ET matter flux to the deep sea based on new and previously published Os isotope data are summarized

Effects of sampling artifacts on cosmic dust flux estimates

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Fig. 2. Blow-up of the extreme left side of the top panel in Fig. 1 showing the quantized nature of frequency distributions upon severe undersampling of the global ET matter flux for very small area–time products (0.00025 m2a). The quantized nature of the frequency distribution results from the small number of ET particles per bin when very small area–time products are used to derive global estimates of the ET matter flux. Note that counts per bin (y-axis) are plotted on a log scale.

Fig. 1. Results of Monte Carlo simulations (n ⫽ 2500) for the fraction of ET matter accreted annually on Earth as a function of sample mass corresponding to area–time products of 0.00025–250 m2a. A normalized ET matter flux of 1 corresponds to 30,000 metric tons per year (Love and Brownlee, 1993). For comparison, the LDEF study by Love and Brownlee (1993) is based on an area–time product of 32 m2a, only slightly larger than the 25 m2a simulation. Nearly all sediment samples previously used for estimating ET matter fluxes to the seafloor correspond to area–time products between 2.5 and 150 m2a and thus, within error, accurately reflect the ET matter flux to Earth.

in Table 1 together with respective area–time products. Bulk and leach data for samples from core 10400 were obtained from 30-g sediment splits, whereas 5 g (bulk) and 10 g (leach) sample splits from DSDP Sites 597 and 598 were used. We used standard analytical techniques to measure leach and bulk Os isotope compositions (e.g., Peucker-Ehrenbrink, 1996; Reusch et al., 1998). Area–time products were calculated from

sediment masses used for Os isotope analyses as well as published data needed to calculate sediment mass accumulation rates (e.g., sedimentation rate, dry bulk density, porosity, grain density). From these data the annual flux of ET matter to the seafloor was calculated using a four-component mixing model. Uncertainties in the flux estimates are dominated by the uncertainties in the isotopic composition of the detrital end-member and the assumption that the leachable Os concentration accurately reflects the concentration of hydrogenous (i.e., seawater derived) Os in the sample (for details of the model and uncertainties in the flux estimates, see Peucker-Ehrenbrink, 1996). Nearly all sediment samples analyzed for Os isotopic composition and used to estimate the ET matter flux correspond to area–time products of ⱖ2.5 m2a (i.e., Domes Site C-13: Esser and Turekian, 1988, 1993; Bauer Basin: Ravizza and McMurtry, 1993; LL44-GPC3 and DSDP Site 596: PeuckerEhrenbrink, 1996; DSDP 597 and 598: Reusch et al., 1998; as well as 10400: this study). On the basis of our model results these samples should faithfully record the ET matter flux to the seafloor. Figure 3 shows a compilation of ET Os concentrations (upper panel) and ET flux estimates (lower panel) plotted against area–time products for the marine sediment samples used in our model. The positive correlation between area–time product and the concentration of ET matter (Fig. 3, upper panel) is caused by generally higher mass accumulation rates of samples characterized by small area–time products, and thus represents a dilution effect of ET matter with detrital/biogenic matter. Individual estimates for the ET matter flux range from 6000 to 100,000 metric tons per year with an average for all samples regardless of area–time product of 32,000 ⫾ 26,000 metric tons per year (1␴, n ⫽ 28, Fig. 3 lower panel). Using only marine sediment samples corresponding to area–time products larger than those used by Love and Brownlee (1993) in their LDEF study that serves as the statistical basis for the above model (i.e., ⬎32 m2a) the global flux of ET matter to the deep sea is 30,000 ⫾ 15,000 metric tons per year (1␴, n ⫽ 5). This estimate is within error but slightly lower than a previ-

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B. Peucker-Ehrenbrink and G. Ravizza Table 1. Four-component Os-isotope mixing model—input and output. Area–time

Sample (site-core, cm)

Ageb (Ma)

10400, 0-5 Replicate 10400, 13-21 10400, 97-114 92-597-3-1, 85-90a 92-598-3-2, 15-20a Replicatea 92-598-3-6, 24-28a 95-598-4-2, 11-15a 92-598-4-6-, 11-14a Replicatea 92-598-5-4, 20-25a 92-598-5-6, 14-17a Replicatea

0.01

12.4

0.06 0.35 18.9 10.96

Bulk sediment

Os Productc (pg/g) (m2a)

187

Os/188Os

12.4 12.4 1.7 4.0

112 152 93 94 38 86

1.0083 ⫾ 0.0012 1.0061 ⫾ 0.0023 0.9876 ⫾ 0.0026 0.9936 ⫾ 0.0037 0.7346 ⫾ 0.0015 0.7910 ⫾ 0.0009

12.17 12.85 14.05

2.1 2.1 4.1

61 82 130

0.7948 ⫾ 0.0013 0.7642 ⫾ 0.0021 0.7655 ⫾ 0.0028

15.28 15.70

3.2 1.6

164 144

0.7426 ⫾ 0.0007 0.7669 ⫾ 0.0008

Os (pg/g)

Leach

Modeling

187

Os IC Xhy Xd XET pg ET Os/g hy %d %d %d (pg/g)

Os/188Os

30

1.0519 ⫾ 0.0013

1.05

31 18 9 12 20 20 20 37 22 69 34 65

1.0296 ⫾ 0.0035 1.0543 ⫾ 0.0016 0.7415 ⫾ 0.0018 0.7913 ⫾ 0.0013 0.7802 ⫾ 0.0012 0.7759 ⫾ 0.0040 0.7636 ⫾ 0.0013 0.7727 ⫾ 0.0028 0.7705 ⫾ 0.0020 0.7584 ⫾ 0.0008 0.7628 ⫾ 0.0014 0.7674 ⫾ 0.0016

1.03 1.03 0.74 0.79 0.78 0.78 0.76 0.77 0.77 0.76 0.76 0.77

27 20 33 20 24 14 23 33 24 28 17 42 24 45

69 76 61 75 52 64 57 51 54 51 50 40 55 39

4 4 6 4 24 22 19 16 21 20 24 18 21 15

4.6 6.5 5.6 4.2 9.2 18.9 16.7 9.9 17.6 26.5 30.6 30.2 30.7 22.2

ET Mattere Flux ⫾ 1␴ (104t/a) 1.2 ⫾ 1.0 1.7 ⫾ 1.4 1.3 ⫾ 0.9 1.3 ⫾ 0.9 5.7 ⫾ 1.9 4.9 ⫾ 1.8 4.3 ⫾ 1.6 2.5 ⫾ 1.0 4.4 ⫾ 1.6 6.8 ⫾ 2.5 7.8 ⫾ 2.7 10.0 ⫾ 3.6 10.4 ⫾ 3.4 7.5 ⫾ 2.7

a

Os isotope data and Os concentrations are from Reusch et al. (1998). All analyses by negative ionization mass spectrometry (NIMA-B, WHOI) after chemical separation and purification of osmium according to methods described in Peucker-Ehrenbrink et al. (1995) and Reusch et al. (1998). 2␴ -uncertainties are given, based on counting statistics. Data are blank, but not age corrected. Total analytical blanks were ⬃1.5 pg/g for bulk sediment analyses (187Os/188Os ⬃ 0.45) and 0.3 pg/g for leaches. b Ages for DSDP 597 and 598 samples are from Reusch et al. (1998), ages for 10400 samples were calculated using a sedimentation rate of 0.3 cm/ka (Colley et al., 1984). c Area-time products were calculated from sample weights, physical property data and sedimentation rates given in Colley et al. (1984) for core 10400 and Reusch et al. (1998) for DSDP Sites 597 and 598. d Percent is given relative to bulk Os concentration. e Uncertainties (1␴) are based on a Monte Carlo simulation with uniform error probability distribution and assumed uncertainties of ⫾50% in mass accumulation rates, ⫾30% in the Os concentration of the leach, variations in the 187Os/188Os of 0.12543– 0.13045 for the extraterrestrial (Meisel et al., 1996) and 1.05–1.3 for the detrital (Peucker-Ehrenbrink and Jahn, unpubl. data) endmembers. Uncertainties in the isotopic composition of contemporaneous sea water are 2–5% depending on the age of the sediment and the precision to which we have reconstructed the marine Os isotope record (for details, see Peucker-Ehrenbrink, 1996). Abbreviations: IC, isotopic composition; hy, hydrogenous; leach, H2O2-H2SO4-soluble; ET, extraterrestrial; d, detrital.

ously published average for the ET matter flux to the deep sea based on sediment bulk-leach Os isotope data pairs available at that time (Peucker-Ehrenbrink, 1996). The main reason for the slightly lower estimate is the use of a somewhat less radiogenic crustal end-member (187Os/188Os of 1.05) in this study compared to previous studies (187Os/188Os of 1.26). The revised global average for the crustal end-member used in this study is based on a study of the Os isotopic composition of worldwide loess deposits as a proxy for eolian dust delivered to the oceans (Peucker-Ehrenbrink and Jahn, 1999). This new estimate of the ET matter flux to the seafloor is in excellent agreement with the estimate derived for the LDEF satellite study (Love and Brownlee, 1993), an additional argument supporting the integrity of Os isotopes as tracers of ET matter in marine sediments. The model results indicate that undersampling the ET matter flux using nonvolatile tracers such as Ir and Os becomes significant when samples corresponding to area–time products of ⬍1 m2a are used. This is the case for lower Ordovician limestone samples analyzed by Schmitz et al. (1997), which correspond to area–time products of ⬇0.25 m2a. Schmitz et al. (1997) have probably undersampled the early Ordovician ET matter flux by ⬇50% if the mass distribution spectrum of ET matter during the Ordovician was similar to the present day. This strengthens their case for one to two orders of magnitude elevated flux of ET matter during a 1 to 2 Ma long interval in the early Ordovician compared to present-day flux estimates. Sampling artifacts associated with two sample types at the extreme ends of the spectrum of mass accumulation rates merit

further discussion—very slowly accumulating Fe–Mn nodules/ crusts and rapidly accumulating snow and ice. Marine ferromanganese nodules and crusts have been widely used as temporal recorders of paleoenvironmental conditions (e.g., Segl et al., 1984; Eisenhauer et al., 1992; Abouchami et al., 1999; Burton et al., 1999). Typical growth rates of such concretions are on the order of a few millimeters per million years. A typical sample of 100 mg, accreted at a rate of 5 mm/Ma with a density of 2 g/cm3, corresponds to an area–time product of 10 m2a, sufficient to adequately sample the ET particle population. With a cosmic dust accretion rate of 30,000 metric tons per year and a CI-chondiritic Os abundance of 486 ng/g (Anders and Grevesse, 1989) such a sample should contain about 2.9 ng/g ET Os with chondritic 187Os/188Os. Existing data for marine Fe–Mn crusts and nodules, however, indicate significantly smaller contributions of ET Os (Turekian and Luck, 1984; Palmer and Turekian, 1986, Palmer et al., 1988; Burton et al., 1999). Despite the fact that individual micrometeorites have been observed in Fe–Mn crusts (Finkelman, 1970, 1972; Jedwab, 1970) and that mixing trends between meteoritic Os and hydrogenous Os have been detected in Fe–Mn crusts (PeuckerEhrenbrink et al., 1997; Burton et al., 1999), ET particles appear to be rarely captured by Fe–Mn crusts/nodules at the seafloor. Finkelman (1970) found “high” (i.e., relative to pelagic sediments) concentrations of up to one ET particle ⬎100 ␮m per gram Fe–Mn nodule. For a 250 ␮m-sized ET particle with a density of 3 g/cm3 and CI-chondritic Os concentration this particle density translates into an ET Os concentration of

Effects of sampling artifacts on cosmic dust flux estimates

Fig. 3. (Top) Area–time products of sediments analyzed for ET matter plotted against estimates of the concentration of ET Os (model results in pg/g from Table 1). Symbols: DSDP 596, filled squares; LL44-GPC3, filled circles; Domes Site C-13, filled cross; Bauer Basin, open upright triangles; DSDP 196, open diamond; DSDP 597/8, open circles; 10400, open squares. (Bottom) Area–time products of sediments analyzed plotted against estimates of the ET matter flux based on Os isotope data for marine sediments (model results from Table 1). Symbols as above. The result from the LDEF cratering study (Love and Brownlee, 1993) is plotted as reference. Note that both area–time products and calculated ET matter flux are functions of the sediment mass accumulation rates and therefore, the two variables are not independent of each other.

only ⬇12 fg/g. The discrepancy between sampling theory and analytical data is suggestive of sampling artifacts resulting from preferential removal of ET particles from nodule/crust surfaces, potentially caused by bottom currents, movement of nodules/crusts by benthic organism or seismic activity, or preferential dissolution of ET particles due to prolonged (i.e., complete burial of a 250 ␮m ET particle in Fe–Mn crusts with growth rates of 5 mm/Ma takes 50,000 yr) exposure to seawater. Such artifacts indicate that ferromanganese nodules/crusts are unsuitable to reconstruct past variations in the accretion rate of ET particles on Earth. Severe undersampling is to be expected for nearly all studies on Ir accumulation in snow and ice (i.e., Rocchia et al., 1990; Rasmussen et al., 1995; Kayser et al., 1998) because typical sample sizes correspond to area–time products of ⬇0.001– 0.005 m2a. ET flux estimates that are based on the assumption that all Ir in ice and snow samples is ET in origin (i.e., placing a firm upper limit on the ET matter flux) are significantly lower (9800 –12,500 metric tons/a: Rocchia et al., 1990; 10,000 ⫾ 2000 metric tons/a: Rasmussen et al., 1995) than those based on Os isotopes in marine sediments. This is consistent with results

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from our model that sampling artifacts for nonvolatile tracers become severe if samples corresponding to area–time products ⱕ 2.5 m2a are used (see Fig. 1). To sample the ET particle population representatively using nonvolatile tracers, snow and ice sample masses of ⬎100 kg are needed. Our model predicts that significantly smaller sample masses will result in large scatter and underestimation of the ET matter flux. Only if atmospheric entry heating leads to redistribution of PGE from individual particles onto multiple small particles (either due to break-up or vaporization followed by recondensation) are the effects of undersampling less severe. Should further analyses of ice and snow samples yield reproducibilities in PGE concentrations much smaller than predicted by our model, redistribution of PGE from individual large particles onto multiple small particles is a likely explanation. Unbiased ET flux estimates based on nonvolatile tracers require sediment/ice core samples corresponding to area–time products of ⱖ2.5 m2a. This requirement places constraints on the smallest detectable frequencies of ET flux oscillations. Typical sediment core samples with a surface area of ⬇10 cm2 that correspond to an area–time product of ⱖ2.5 m2a integrate over ⱖ2500 yr of sediment deposition. Oscillations in the ET matter flux to Earth on time scales shorter than 2500 yr (25,000 yr for area–time products of 25 m2a) cannot be detected from typical sediment/ice core samples. Only samples representing much larger surface areas, such as snow pit samples, box core samples, and continuous melting of ice caverns (e.g., Taylor et al., 1998), yield sufficient time resolution to detect flux oscillations on decadal to millennial time scales. The presence of long frequency oscillations in the ET matter flux such as on glacial–interglacial (i.e., 100,000 yr) time scales, however, are detectable by down-core analyses of sediment and ice core samples. 5. CONCLUSIONS

We have demonstrated the integrity of estimates of the global flux of ET matter based on nonvolatile tracers such as Os in marine sediments. The global flux of ET matter to the seafloor, calculated at 30,000 ⫾ 15,000 metric tons per year using Os isotope data for the most suitable marine sediment samples, agrees with the flux of ET matter derived from the LDEF study (40,000 ⫾ 20,000 metric tons per year; Love and Brownlee, 1993) within uncertainty. This flux is too small to significantly impact the Os isotopic composition of seawater (Peucker-Ehrenbrink, 1996). The probability for undersampling the ET particle population increases as samples corresponding to area–time products of ⬍2.5 m2a are used to estimate the flux of ET matter to Earth. Snow and ice samples are most prone to this statistical bias. Acknowledgments—We thank Mark Kurz for his advice, and Brad Esser and Karl Turekian for information on sample weights used for previously published Os isotope analyses. John Thomson generously supplied large (30 g) sample splits from core 10400 for Os isotope analyses. Stan Hart provided access to his clean laboratory and NIMA-B for Os isotope analyses—thanks, Stan! We very much appreciate comments by Brad Esser who encouraged us to discuss sampling artifacts associated with Fe–Mn crusts, and Ken Farley, whom we thank for his cooperation in cross-checking our model results and for pointing out the potential importance of PGE redistribution upon atmospheric entry. Financial support was provided by the NSF-

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B. Peucker-Ehrenbrink and G. Ravizza

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