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Probability of Causation for Space Radiation Carcinogenesis Following International Space Station, Near Earth Asteroid, and Mars Missions

Cancer risk is an important concern for International Space Station (ISS) missions and future exploration missions. An important question concerns the likelihood of a causal association between a crew members radiation exposure and the occurrence of cancer. The probability of causation (PC), also denoted as attributable risk, is used to make such an estimate. This report summarizes the NASA model of space radiation cancer risks and uncertainties, including improvements to represent uncertainties in tissue-specific cancer incidence models for never-smokers and the U.S. average population. We report on tissue-specific cancer incidence estimates and PC for different post-mission times for ISS and exploration missions. An important conclusion from our analysis is that the NASA policy to limit the risk of exposure-induced death to 3% at the 95% confidence level largely ensures that estimates of the PC for most cancer types would not reach a level of significance. Reducing uncertainties through radiobiological research remains the most efficient method to extend mission length and establish effective mitigators for cancer risks. Efforts to establish biomarkers of space radiation-induced tumors and to estimate PC for rarer tumor types are briefly discussed.

Cucinotta, Francis A.↗

Histogrammatic Method for Determining Relative Abundance of Input Gas Pulse

To satisfy the Major Constituents Analysis (MCA) requirements for the Vehicle Cabin Atmosphere Monitor (VCAM), this software analyzes the relative abundance ratios for N2, O2, Ar, and CO2 as a function of time and constructs their best-estimate mean. A histogram is first built of all abundance ratios for each of the species vs time. The abundance peaks corresponding to the intended measurement and any obfuscating background are then separated via standard peak-finding techniques in histogram space. A voting scheme is then used to include/exclude this particular time sample in the final average based on its membership to the intended measurement or the background population. This results in a robust and reasonable estimate of the abundance of trace components such as CO2 and Ar even in the presence of obfuscating backgrounds internal to the VCAM device. VCAM can provide a means for monitoring the air within the enclosed environments, such as the ISS (International Space Station), Crew Exploration Vehicle (CEV), a Lunar Habitat, or another vehicle traveling to Mars. Its miniature pre-concentrator, gas chromatograph (GC), and mass spectrometer can provide unbiased detection of a large number of organic species as well as MCA analysis. VCAM s software can identify the concentration of trace chemicals and whether the chemicals are on a targeted list of hazardous compounds. This innovation s performance and reliability on orbit, along with the ground team s assessment of its raw data and analysis results, will validate its technology for future use and development.

Mandrake, Lukas↗

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗

Evaluation of Modeling NO2 Concentrations Driven by Satellite-Derived and Bottom-Up Emission Inventories Using In-Situ Measurements Over China

Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slopeD0.74 and 0.64 for the daily mean and daytime only) and the MIX (slopeD1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10-40% higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of -30 to 0% on average and more firmly establishes that the MIX inventory is biased high over major cities. The performance of the model is comparable over seasons, with a slightly worse spatial correlation in summer due to the difficulties in resolving the more active NOx photochemistry and larger concentration gradients in summer by the model. In addition, the model well captures the daytime diurnal cycle but shows more significant disagreement between simulations and measurements during nighttime, which likely produces a positive model bias of about 15% in the daily mean concentrations. This is most likely related to the uncertainty in vertical mixing in the model at night.

NO2 modelling↗

Comparison of Pre- and Post-Flight Estimations of Pitch Damping Coefficients for Unguided Entry Vehicles

Pre-flight predictions of pitch damping coefficient (C M q + C m ȧ ) curves are used in entry simulations to determine flight readiness and if any dynamic remediation strategies are required. Accurate characterization of these pitch damping coefficient curves is crucial for mission success. Historically, pre-flight estimations of these curves are derived experimentally either via ballistic range testing or with 1-degree-of-freedom (DOF) free-or forced-oscillation wind tunnel testing. With post-flight best-estimated trajectories, a fitting procedure as described in Karlgaard, et. al. is used to compare pre-and post-flight pitch damping coefficients. This technique relies on an assumed analytical form of the trajectory, a limited 3-DOF representation described in Schoenenberger and Queen, which results in an Euler-Cauchy solution form. This solution assumes constant density, thus limited amplitude multi-peak windows of the trajectory are considered to populate the pitch damping-amplitudes pace. The estimated post-flight pitch damping approximations and the pre-flight predictions shown are effective representations of pitch damping, or the integrated effect of the pitch damping coefficient over one pitch cycle at the corresponding cycle’s peak amplitude. Effective pitch damping coefficient curves provide more intuitive insights about where the vehicle is stable and permits readily processed comparisons between data-sets. It is important to note that most pitch damping curves, such as those reported in aero databases and utilized in flight mechanics trajectory simulations, are represented in instantaneous angle-of-attack space distinct from what is presented in the paper.

pitch damping coefficient↗

SupportU: Smart UAS Program for the Population by Offering Resources and Tools to the Unhoused

Global warming, challenging economic conditions, the opioid epidemic, and other widespread problems, have impacted people globally, particularly over the past several years. Preventable diseases like the common cold and the effects of heat stroke have become increasingly prevalent due to these issues. It is estimated that 150 million people of the world’s population are unhoused globally, with many dwelling in unsafe and unsanitary conditions while lacking access to basic hygienic items and other essentials. Unsanitary conditions coupled with this lack of access exacerbates and prolongs health problems and harms quality of life. Traditional methods of aid, such as homeless shelters and meal programs, face numerous challenges such as having limited reach and resources. To address these problems, the Smart UAS Program for the Population by Offering Resources and Tools to the Unhoused (SUPPORT U) utilizes Uncrewed Aircraft Systems (UAS) to deliver resources to the unhoused and those in need of basic aid, prior to and during extreme temperature conditions, and after natural disasters in rural, suburban, and urban areas. The UA is envisioned to be an autonomous aircraft capable of efficiently distributing essential supplies, including blankets, water, food, and medicine. The UAS fleet relies on advanced navigation and communication technologies to accurately identify unhoused people and efficiently and safely distribute materials to them. This will be done through a machine learning algorithm. By focusing on identified “homeless clusters”, places where unhoused individuals are concentrated, the UAS network increases access to critical resources, thereby helping to mitigate some of the external risks to the health of unhoused individuals. The UA can also be used during crises, such as by transporting supplies to medical tents that are stationed in difficult-to-reach areas suffering from natural disasters.

Samuel Beard↗

Cratering time scales for the Galilean satellites

An attempt is made to estimate the present cratering rate for each Galilean satellite within the correct order of magnitude and to extend the cratering rates back into the geologic past on the basis of evidence from the earth-moon system. For collisions with long and short period comets, the magnitudes and size distributions of the comet nuclei, the distribution of their perihelion distances, and the completeness of discovery are addressed. The diameters and masses of cometary nuclei are assessed, as are crater diameters and cratering rates. The dynamical relations between long period and short period comets are discussed, and the population of Jupiter-crossing asteroids is assessed. Estimated present cratering rates on the Galilean satellites are compared and variations of cratering rate with time are considered. Finally, the consistency of derived cratering time scales with the cratering record of the icy Galilean satellites is discussed.

Shoemaker, E. M.↗

Chromosome Aberrations in Astronauts

A review of currently available data on in vivo induced chromosome damage in the blood lymphocytes of astronauts proves that, after protracted exposure of a few months or more to space radiation, cytogenetic biodosimetry analyses of blood collected within a week or two of return from space provides a reliable estimate of equivalent radiation dose and risk. Recent studies indicate that biodosimetry estimates from single spaceflights lie within the range expected from physical dosimetry and biophysical models, but very large uncertainties are associated with single individual measurements and the total sample population remains low. Retrospective doses may be more difficult to estimate because of the fairly rapid time-dependent loss of "stable" aberrations in blood lymphocytes. Also, biodosimetry estimates from individuals who participate in multiple missions, or very long (interplanetary) missions, may be complicated by an adaptive response to space radiation and/or changes in lymphocyte survival and repopulation. A discussion of published data is presented and specific issues related to space radiation biodosimetry protocols are discussed.

George, Kerry A.↗

Optimized O'Neill/Glaser Model for Human Population of Space and its Impact on Survival Probabilities

Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth's carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.

Curreri, Peter A.↗

Optimized O'Neill/Glaser Model for Human Population of Space and its Impact on Survival Probabilities

Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth s carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.

Curreri, Peter A.↗

Optimized O'Neill/Glaser Model for Human Population of Space and its Impact on Survival Probabilities

Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth s carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O'Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.

Curreri, Peter A.↗

Semi-Analytic Forecasts for JWST– V. AGN Luminosity Functions and Helium Reionization at z= 2–7

Active galactic nuclei (AGN) forming in the early universe are thought to be the pri-mary source of hard ionizing photons contributing to the reionization of intergalactic helium. However, the number density and spectral properties of high-redshift AGN remain largely unconstrained. In this work, we make use of physically-informed mod-els calibrated with a wide variety of available observations to provide estimates for the role of AGN throughout the Epoch of Reionization. We present AGN luminosity functions in various bands between z= 2 to 7 predicted by the well-established Santa Cruz semi-analytic model, which includes modelling of black hole accretion and AGN feedback. We then combine the predicted AGN populations with a physical spectral model for self-consistent estimates of ionizing photon production rates, which depend on the mass and accretion rate of the accreting supermassive black hole. We then couple the predicted comoving ionizing emissivity with an analytic model to compute the subsequent reionization history of intergalactic helium and hydrogen. This work demonstrates the potential of coupling physically motivated analytic or semi-analytic techniques to capture multi-scale physical processes across a vast range of scales (here, from AGN accretion disks to cosmological scales). Our physical model predicts an in-trinsic ionizing photon budget well above many of the estimates in the literature, meaning that helium reionization can comfortably be accomplished even with a rel-atively low escape fraction. We also make predictions for the AGN populations that are expected to be detected in future James Webb Space Telescope surveys

L Y Aaron Yung↗

Gamma-ray burst constraints on the galactic frequency of extrasolar Oort Clouds

With the strong Compton Gamma-Ray Observatory/Burst and Transient Source Experiment (CGRO/BATSE) evidence that most gamma-ray bursts do not come from galactic neutron stars, models involving the accretion of a comet onto a neutron star (NS) no longer appear to be strong contenders for explaining the majority of bursts. If this is the case, then it is worth asking whether the lack of an observed galactic gamma-ray burst population provides a useful constraint on the number of comets and comet clouds in the galaxy. Owing to the previously unrecognized structural weakness of cometary nuclei, we find the capture cross sections for comet-NS events to be much higher than previously published estimates, with tidal breakup at distances R(sub b) approx. equals 4 x 10(exp 10) cm from the NS. As a result, impacts of comets onto field NSs penetrating the Oort Clouds of other stars are found to dominate all other galactic NS-comet capture rates by a factor of 100. This in turn predicts that if comet clouds are common, there should be a significant population of repeater sources with (1) a galactic distribution, (2) space-correlated repetition, and (3) a wide range of peak luminosities and luminosity time histories. If all main sequence stars have Oort Clouds like our own, we predict approximately 4000 such repeater sources in the Milky Way at any time, each repeating on time scales of months to years. Based on estimates of the sensitivity of the CGRO/BATSE instrument and assuming isotropic gamma-ray beaming from such events, we estimate that a population of approximately 20-200 of these galactic NS-Oort Cloud gamma-ray repeater sources should be detectable by CGRO. In addition, if giant planet formation is common in the galaxy, we estimate that the accretion of isolated comets injected to the interstellar medium by giant planet formation should produce an additional source of galactic, nonrepeating, events. Comparing these estimates to the 3-4 soft gamma-ray repeater sources detected by BATSE, one is forced to conclude that (1) comet impacts on NSs are inefficient at producing gamma rays; or (2) the gamma rays from such events are highly beamed; or (3) the fraction of stars in the galaxy with Oort Clouds like our own is not higher than a few percent.

Shull, J. Michael↗

Gamma-ray burst constraints on the galactic frequency of extra-solar Oort clouds

With the strong CGRO/BATSE evidence that most gamma-ray bursts do not come from galactic neutron stars, models involving the accretion of a comet onto a neutron star (NS) no longer appear to be strong contenders for explaining the majority of bursts. If this is the case, then it is worth asking whether the lack of an observed galactic gamma-ray burst population provides a useful constraint on the number of comets and comet clouds in the galaxy. Owing to the previously unrecognized structural weakness of cometary nuclei, we find the capture cross sections for comet-NS events to be much higher than previously published estimates, with tidal breakup at distances R(sub b) approximately equals to 4 x 10(exp 10) cm from the NS. As a result, impacts of comets onto field NS's penetrating the Oort Clouds of other stars are found to dominate all other galactic NS-comet capture rates by a factor of 100. This in turn predicts that if comet clouds are common, there should be a significant population of repeater sources with (1) a galactic distribution, (2) space-correlated repetition, and (3) a wide range of peak luminosities and luminosity time histories. If all main sequences stars have Oort Clouds like our own, we predict approximately 4000 such repeater sources in the Milky Way at any time, each repeating on timescales of months to years. Based on estimates of the sensitivity of the CGRO/BATSE instrument and assuming isotropic gamma-ray beaming from such events, we estimate that a population of approximately 20-200 of these galactic NS-Oort Cloud gamma-ray repeater sources should be detectable by CGRO. In addition, if giant planet formation is common in the galaxy, we estimate that the accretion of isolated comets injected to the interstellar medium by giant planet formation should produce an additional source of galactic, nonrepeating events. Comparing these estimates to the three to four soft gamma-ray repeater sources detected by BATSE, one is forced to conclude that (1) comet impacts on NS's are inefficient at producing gamma-rays; or (2) the gamma-rays from such events are highly beamed; or (3) the fraction of stars in the galaxy with Oort Cloud like our own is not higher than a few percent.

Shull, J. Michael↗

Inference of a 7.75 eV lower limit in the ultraviolet pumping of interstellar polycyclic aromatic hydrocarbon cations with resulting unidentified infrared emissions

The discrete infrared features known as the unidentified infrared (UIR) bands originating in starburst regions of other galaxies, and in H II regions and planetary nebulae within the Milky Way, are widely thought to be the result of ultraviolet pumped infrared fluorescence of polycyclic aromatic hydrocarbon (PAH) molecules and ions. These UIR emissions are estimated to account for 10%-30% of the total energy emitted by galaxies. Laboratory absorption spectra including the vacuum ultraviolet region, as described in this paper, show a weakening of the intensity of absorption features as the population of cations increases, suggesting that strong pi* <-- pi transitions are absent in the spectra of PAH cations. This implies a lower energy bound for ultraviolet photons that pump infrared emissions from such ions at 7.75 eV, an amount greater than previously thought. The implications include size and structure limitations on the PAH molecules and ions which are apparent constituents of the interstellar medium. Also, this might affect estimations of the population of early-type stars in regions of rapid star formation.

Non-NASA Center↗