Mathematics – Logic
Scientific paper
Jan 1999
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1999nvm..confr..59s&link_type=abstract
Workshop on New Views of the Moon 2: Understanding the Moon Through the Integration of Diverse Datasets, p. 59
Mathematics
Logic
Basalt, Breccia, Crusts, Lunar Geology, Lunar Maria, Lunar Rocks, Lunar Surface, Magma, Titanium Oxides, Volcanology, Lunar Crust, Clementine Spacecraft, Craters, Galileo Spacecraft, Radiometers, Remote Sensing, Lunar Mantle
Scientific paper
It has long been recognized that the lunar-sample suite returned by the Apollo and Luna missions is biased with regard to its representation of lunar mare basalts. This sampling bias is reflected in both an incorrect portrayal of the volume of mare basalt types and the absence of many basalt groups known to exist from spectral data. This bias obviously affects models for the petrogenesis of mare basalts and the interior of the Moon. Here, we explore the implications of this bias and compare models for lunar magmatism that are derived solely from samples with potential models derived from combined sample and remote-sensing data. We focus on the implications of these contrasts in several areas: volume, distribution, and age of mare basalts, KREEP enrichment on the nearside of the Moon, heat sources for melting, and depth of mare basalt source regions. The mare basalt sample suite indicates that the TiO2 distribution of crystalline mare basalt samples is bimodal, with a majority of the mare basalts occurring in the range of 1.5-5.5 and 10-13 wt% TiO2. A compositional gap appears to exist between 6 and 9 wt% TiO2. Although the population of picritic mare glasses also exhibits a bimodal distribution with regard to Ti02, it is dominated by very low-Ti glasses (<1 wt% TiO2) and high-Ti glasses (8-16 wt% TiO2) and exhibits a very broad compositional gap between 1 and 8 wt% Ti02. The simplest interpretation of the bimodal Ti distribution is that two distinct sources were melted to produce the mare basalts: late, rather shallow, Ti-rich lunar magma ocean (LMO) cumulates and early, rather deep, Ti-poor LMO cumulates. More recently, on the basis of Galileo SSI and Clementine UV-VIS data, global TiO2 distribution has been interpreted to be continuous in the maria with no hint of biomodality and an abundance peak between I and 3.5 wt% TiO2. These new observations indicate a mare source model in which a small volume of late, ilmenite-bearing LMO cumulates mixed with a large volume of early LMO cumulates in which ilmenite was absent. These differences in models have implications for heat sources for generating mare basalts, the relative depth of various mare basalt sources, and the early dynamics of the lunar mantle. Although remote optical and spectral observations of the lunar surface document the concentration of mare basalts on the nearside of the Moon our limited sampling of basalts does not define the overall distribution of mare basalt compositions. The relative distribution of high-Ti basalts should shed light on the asymmetry of LMO cumulates and refine or refute mare basalt models that require recycling of late, high-Ti cumulates into the deep lunar mantle. Lunar pyroclastic glasses have been identified at all of the Apollo sites, Based on samples, the compositional variation of these glasses is bimodal and their overall abundance is unknown. Understanding both their compositional diversity and distribution is critical to deciphering how these near-primary magmas were transported to the lunar surface from great depths and how they are related to crystalline mare basalts. Based on Clementine data and previous work, more than 100 lunar pyroclastic deposits have been proposed and potentially a large number consist of high-Ti glass beads. The existence of so many deposits that could consist of near-primary basaltic magmas implies that mechanisms for their transport to the surface are not extraordinary and that density contrasts between melts and surrounding mantle do not significantly impede their source segregation and movement, at high pressure, to the lunar surface. Age of mare basalt groups. While radiometric age dating of lunar mare basalts provides a precise means of dating individual samples, when it is combined with relative age relationships determined by remote sensing (e.g., crater counts) it becomes a method for reconstructing magmatism on a planetary scale. Two examples where this approach has provided useful information and will continue to bear fruit are the duration and early history of lunar volcanism and the relationship between mare basalt composition and eruptive history. Although the petrologic record has been obscured by the early catastrophic impact history of the Moon, there is abundant evidence of pre-3.9 Ga nonmare basaltic volcanism [e.g., 7-8]. Most of this record is retained in small clasts from highland soils and breccias or has been identified through remote sensing. The relationship between the samples and units identified through remote sensing is speculative. Further identification and delineation of older episodes of volcanism and their relationship to episodes of crustal plutonism (Mg and alkali suites) is critical to our interpretation of mantle evolution following magma ocean crystallization and prior to the onset of mare volcanism. Combined sample and remote sensing data sets will allow us to better distinguish among the wide range of models that have been proposed for these early periods of lunar magmatism (Mg suite, alkali suite, KREEP basalts). These models include (1) impact origin; (2) magma ocean crystallization; (3) melting and remobilization of late magma ocean cumulates and/or KREEP infiltrated lower crust; (4) melting of the lower portions of the cumulate pile followed by assimilation of KREEP or anorthositic crust; and (5) melting of deep, hybrid mixed cumulate sources. Additional information is contained in the original.
Gaddis Lisa R.
Papike James J.
Shearer Charles K.
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