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Statistical Issues for Uncontrolled Reentry Hazards
A number of statistical tools have been developed over the years for assessing the risk of reentering objects to human populations. These tools make use of the characteristics (e.g., mass, shape, size) of debris that are predicted by aerothermal models to survive reentry. The statistical tools use this information to compute the probability that one or more of the surviving debris might hit a person on the ground and cause one or more casualties. The statistical portion of the analysis relies on a number of assumptions about how the debris footprint and the human population are distributed in latitude and longitude, and how to use that information to arrive at realistic risk numbers. This inevitably involves assumptions that simplify the problem and make it tractable, but it is often difficult to test the accuracy and applicability of these assumptions. This paper looks at a number of these theoretical assumptions, examining the mathematical basis for the hazard calculations, and outlining the conditions under which the simplifying assumptions hold. In addition, this paper will also outline some new tools for assessing ground hazard risk in useful ways. Also, this study is able to make use of a database of known uncontrolled reentry locations measured by the United States Department of Defense. By using data from objects that were in orbit more than 30 days before reentry, sufficient time is allowed for the orbital parameters to be randomized in the way the models are designed to compute. The predicted ground footprint distributions of these objects are based on the theory that their orbits behave basically like simple Kepler orbits. However, there are a number of factors - including the effects of gravitational harmonics, the effects of the Earth's equatorial bulge on the atmosphere, and the rotation of the Earth and atmosphere - that could cause them to diverge from simple Kepler orbit behavior and change the ground footprints. The measured latitude and longitude distributions of these objects provide data that can be directly compared with the predicted distributions, providing a fundamental empirical test of the model assumptions.
Empirical Tests of the Predicted Footprint for Uncontrolled Satellite Reentry Hazards
A number of statistical tools have been developed over the years for assessing the risk of reentering object to human populations. These tools make use of the characteristics (e.g., mass, material, shape, size) of debris that are predicted by aerothermal models to survive reentry. The statistical tools use this information to compute the probability that one or more of the surviving debris might hit a person on the ground and cause one or more casualties. The statistical portion of the analysis relies on a number of assumptions about how the debris footprint and the human population are distributed in latitude and longitude, and how to use that information to arrive at realistic risk numbers. Because this information is used in making policy and engineering decisions, it is important that these assumptions be tested using empirical data. This study uses the latest database of known uncontrolled reentry locations measured by the United States Department of Defense. The predicted ground footprint distributions of these objects are based on the theory that their orbits behave basically like simple Kepler orbits. However, there are a number of factors in the final stages of reentry - including the effects of gravitational harmonics, the effects of the Earth s equatorial bulge on the atmosphere, and the rotation of the Earth and atmosphere - that could cause them to diverge from simple Kepler orbit behavior and possibly change the probability of reentering over a given location. In this paper, the measured latitude and longitude distributions of these objects are directly compared with the predicted distributions, providing a fundamental empirical test of the model assumptions.
Statistical Issues for Uncontrolled Reentry Hazards Empirical Tests of the Predicted Footprint for Uncontrolled Satellite Reentry Hazards
A number of statistical tools have been developed over the years for assessing the risk of reentering objects to human populations. These tools make use of the characteristics (e.g., mass, material, shape, size) of debris that are predicted by aerothermal models to survive reentry. The statistical tools use this information to compute the probability that one or more of the surviving debris might hit a person on the ground and cause one or more casualties. The statistical portion of the analysis relies on a number of assumptions about how the debris footprint and the human population are distributed in latitude and longitude, and how to use that information to arrive at realistic risk numbers. Because this information is used in making policy and engineering decisions, it is important that these assumptions be tested using empirical data. This study uses the latest database of known uncontrolled reentry locations measured by the United States Department of Defense. The predicted ground footprint distributions of these objects are based on the theory that their orbits behave basically like simple Kepler orbits. However, there are a number of factors in the final stages of reentry - including the effects of gravitational harmonics, the effects of the Earth s equatorial bulge on the atmosphere, and the rotation of the Earth and atmosphere - that could cause them to diverge from simple Kepler orbit behavior and possibly change the probability of reentering over a given location. In this paper, the measured latitude and longitude distributions of these objects are directly compared with the predicted distributions, providing a fundamental empirical test of the model assumptions.
Statistical Issues for Calculating Reentry Hazards
A number of statistical tools have been developed over the years for assessing the risk of reentering object to human populations. These tools make use of the characteristics (e.g., mass, shape, size) of debris that are predicted by aerothermal models to survive reentry. This information, combined with information on the expected ground path of the reentry, is used to compute the probability that one or more of the surviving debris might hit a person on the ground and cause one or more casualties. The statistical portion of this analysis relies on a number of assumptions about how the debris footprint and the human population are distributed in latitude and longitude, and how to use that information to arrive at realistic risk numbers. This inevitably involves assumptions that simplify the problem and make it tractable, but it is often difficult to test the accuracy and applicability of these assumptions. This paper builds on previous IAASS work to re-examine many of these theoretical assumptions, including the mathematical basis for the hazard calculations, and outlining the conditions under which the simplifying assumptions hold. This study also employs empirical and theoretical information to test these assumptions, and makes recommendations how to improve the accuracy of these calculations in the future.
Statistical Issues for Calculating Reentry Hazards
A number of statistical tools have been developed over the years for assessing the risk of reentering object to human populations. These tools make use of the characteristics (e.g., mass, shape, size) of debris that are predicted by aerothermal models to survive reentry. This information, combined with information on the expected ground path of the reentry, is used to compute the probability that one or more of the surviving debris might hit a person on the ground and cause one or more casualties. The statistical portion of this analysis relies on a number of assumptions about how the debris footprint and the human population are distributed in latitude and longitude, and how to use that information to arrive at realistic risk numbers. This inevitably involves assumptions that simplify the problem and make it tractable, but it is often difficult to test the accuracy and applicability of these assumptions. This paper builds on previous IAASS work to re-examine one of these theoretical assumptions.. This study employs empirical and theoretical information to test the assumption of a fully random decay along the argument of latitude of the final orbit, and makes recommendations how to improve the accuracy of this calculation in the future.
Using Deep Mutational Data and Machine Learning to Guide Outbreak and Pandemic Response
A significant fraction of pathogens known to infect humans originate in non-human (zoonotic) hosts (Taylor, Latham, and Woolhouse 2001), and new and emerging pathogens continue to spill over into the human population more frequently at an alarming rate (e.g., SARS, MERS, Cholera, etc.). The recent outbreaks of Ebola virus in West Africa and the ongoing SARS-CoV-2 pandemic demonstrate the need for rapid and reliable assessments of viral phenotype information to help inform scientists and policy makers how best to control the spread of disease. Further understanding of the virus pathogenic evolutionary space and potential trajectory could guide appropriate control measures to limit the spread of a new virus throughout the local and global human population.
Atm heterozygous mice are more sensitive to radiation-induced cataracts than are their wild-type counterparts
It is important to know whether the human population includes genetically predisposed radiosensitive subsets. In vitro studies have shown that cells from individuals homozygous for ataxia telangiectasia (A-T) are much more radiosensitive than cells from unaffected individuals. Although cells heterozygous for the ATM gene (ATM(+/-)) may be slightly more radiosensitive in vitro, it remained to be determined whether the greater susceptibility of ATM(+/-) cells translates into an increased sensitivity for late effects in vivo, though there is a suggestion that radiotherapy patients that are heterozygous for the ATM gene may be more at risk of developing late normal tissue damage. We chose cataractogenesis in the lens as a means to assay for the effects of ATM deficiency in a late-responding tissue. One eye of wild-type, Atm heterozygous and homozygous knockout mice was exposed to 0.5-, 1.0-, 2.0-, or 4.0-Gy x rays. The animals were followed weekly for cataract development by conventional slit-lamp biomicroscopy. Cataract development in the animals of all three groups was strongly dependent on dose. The lenses of homozygous mice were the first to opacify at any given dose. Most important in the present context is that cataracts appeared earlier in the heterozygous versus wild-type animals. The data suggest that ATM heterozygotes in the human population may also be radiosensitive. This may influence the choice of individuals destined to be exposed to higher than normal doses of radiation, such as astronauts, and may also suggest that radiotherapy patients who are ATM heterozygotes could be predisposed to increased late normal tissue damage.
Establishing the Global Fresh Water Sensor Web
This paper presents an approach to measuring the major components of the water cycle from space using the concept of a sensor-web of satellites that are linked to a data assimilation system. This topic is of increasing importance, due to the need for fresh water to support the growing human population, coupled with climate variability and change. The net effect is that water is an increasingly valuable commodity. The distribution of fresh water is highly uneven over the Earth, with both strong latitudinal distributions due to the atmospheric general circulation, and even larger variability due to landforms and the interaction of land with global weather systems. The annual global fresh water budget is largely a balance between evaporation, atmospheric transport, precipitation and runoff. Although the available volume of fresh water on land is small, the short residence time of water in these fresh water reservoirs causes the flux of fresh water - through evaporation, atmospheric transport, precipitation and runoff - to be large. With a total atmospheric water store of approx. 13 x 10(exp 12)cu m, and an annual flux of approx. 460 x 10(exp 12)cu m/y, the mean atmospheric residence time of water is approx. 10 days. River residence times are similar, biological are approx. 1 week, soil moisture is approx. 2 months, and lakes and aquifers are highly variable, extending from weeks to years. The hypothesized potential for redistribution and acceleration of the global hydrological cycle is therefore of concern. This hypothesized speed-up - thought to be associated with global warming - adds to the pressure placed upon water resources by the burgeoning human population, the variability of weather and climate, and concerns about anthropogenic impacts on global fresh water availability.
Accelerating growth of human coastal populations at the global and continent levels: 2000–2018
Not provided.
LandScan Global 30 Arcsecond Annual Global Gridded Population Datasets from 2000 to 2022
Abstract Oak Ridge National Laboratory (ORNL) annually develops the LandScan Global (LSG) dataset, a 30 arcsecond global gridded population dataset representing global ambient human population distribution. This multivariable dasymetric model disaggregates census counts within administrative boundaries using ancillary data. Each country’s distribution reflects cultural and socioeconomic patterns; manual validations yield a unique global dataset for assessing populations at risk. For over two decades, LSG has been a standard for estimating populations at risk, aiding U.S. federal government, academia and humanitarian organizations. During disasters such as the 2004 Indian Ocean tsunami and the 2010 Haiti earthquake and geopolitical crises such as the Syrian civil war and the 2022 Russian invasion of Ukraine, LSG supported scientific and operational communities in emergency response and recovery. In 2022, LSG datasets from 2000 onward were made publicly available through ORNL’s LandScan Portal. This data descriptor details our methodology and the application of geospatial science and machine learning to geographic and demographic data, highlighting uses in urban resiliency, emergency management, disaster response, and human health and security.
Future Exponential Economic Growth in Space
The human population and economy are now limited by the land area, materials and energy available on Earth. As explained by Malthus, human effort can increase this population limit only gradually and linearly at any fixed level of technology. The unexpected exponential increase in population since Malthus time is due to the even greater exponential increase in agricultural and industrial productivity due to modern technology. Current opinion is divided between the limiters who see fast approaching unavoidable limits to growth and growthers who expect continuing innovation and expansion. Given the minimum energy and food needed to support each human, the population of Earth is necessarily bounded. The past human exponential expansions were based on the invention of agriculture and industry. Continued expansion could occur with future colonization of the solar system. The initial occupation of near-Earth space would probably be for immediate military and economic gains rather than to escape the limits to growth on Earth. Space habitats could exploit solar system energy, materials, and living space, first in the Earth-moon system and later throughout the solar system. Space habitats would be supported by robotic power stations, mining, manufacturing, and transportation. These could travel to the stars with the addition of propulsion and nuclear power. Human expansion into the galaxy would allow continuing exponential growth and could establish a vast interconnected galactic civilization.
Quantifying Impacts of Renewable Electricity Deployment on Air Quality and Human Health in Southeast Asia Based on AIMS III Scenarios
This study augments the ASEAN Interconnection Masterplan Study III (AIMS III) by quantifying changes to air quality and human health that result from its renewable integration and transmission interconnection scenarios. Performing this analysis requires translation of the changes in projected generation from different power sector fuel sources in the AIMS III scenarios to changes in air pollutant emissions, developing what is known as an emissions inventory for each scenario and year evaluated. An emissions inventory represents who emits air pollutants, from where the pollutants are emitted, when, and how much of which air pollutants are emitted. With the assistance of the ASEAN Centre for Energy and leveraging the best available in-region public data sources, the National Renewable Energy Laboratory (NREL) team compiled a detailed inventory of power plants in the ASEAN region, mapping their PM 2.5 , sulfur oxides (SOx), and nitrogen oxides (NOx) emissions. A new, first-of-its-kind, and user-friendly global air quality model, Global InMAP (Thakrar et al. 2022), is then used to transform the inventory of changes in emissions to changes in concentration of fine particulate matter. Global InMAP then maps the location of human populations in ASEAN countries to calculate humans' exposure to PM 2.5 and estimate excess PM 2.5 -caused mortality attributable to thermal generation sources, as modeled in the AIMS III scenarios.
It's All Relative: A Validation of Radiation Quality Comparison Metrics
The difference between high-LET and low-LET radiation is quantified by a measure called relative biological effectiveness (RBE). RBE is defined as the ratio of the dose of a reference radiation to that of a test radiation to achieve the same effect level, and thus, is described either as an iso-effector dose-to-dose ratio. A single dose point is not sufficient to calculate an RBE value; therefore, studies with only one dose point usually calculate an effect-to-effect ratio. While not formally used in radiation protection, these iso-dose values may still be informative. Shuryak, et al 2017 investigated the use of an iso-dose metric termed "radiation effects ratio" (RER) and used both RBE and RER to estimate high-LET risks. To apply RBE or RER to risk prediction, the selected metric must be uniquely defined. That is, the calculated value must be consistent within a model given a constant set of constraints and assumptions, regardless of how effects are defined using statistical transformations from raw endpoint data. We first test the RBE and the RER to determine whether they are uniquely defined using transformations applied to raw data. Then, we test whether both metrics can predict heavy ion response data after simulated effect size scaling between human populations or when converting animal to human endpoints.
Population Growth in Man and Its Consequences
Sociological implications of human population explosion and technological and food production
Musing over Microbes in Microgravity: Microbial Physiology Flight Experiment
New York City, the most populated city in the United States, is home to over 8 million humans. This means over 26,000 people per square mile! Imagine, though, what the view would be if you peeked into the world of microscopic organisms. Scientists estimate that a gram of soil may contain up to 1 billion of these microbes, which is as much as the entire human population of China! Scientists also know that the world of microbes is incredibly diverse-possibly 10,000 different species in one gram of soil - more than all the different types of mammals in the world. Microbes fill every niche in the world - from 20 miles below the Earth's surface to 20 miles above, and at temperatures from less than -20 C to hotter than water's boiling point. These organisms are ubiquitous because they can adapt quickly to changing environments, an effective strategy for survival. Although we may not realize it, microbes impact every aspect of our lives. Bacteria and fungi help us break down the food in our bodies, and they help clean the air and water around us. They can also cause the dark, filmy buildup on the shower curtain as well as, more seriously, illness and disease. Since humans and microbes share space on Earth, we can benefit tremendously from a better understanding of the workings and physiology of the microbes. This insight can help prevent any harmful effects on humans, on Earth and in space, as well as reap the benefits they provide. Space flight is a unique environment to study how microbes adapt to changing environmental conditions. To advance ground-based research in the field of microbiology, this STS-107 experiment will investigate how microgravity affects bacteria and fungi. Of particular interest are the growth rates and how they respond to certain antimicrobial substances that will be tested; the same tests will be conducted on Earth at the same times. Comparing the results obtained in flight to those on Earth, we will be able to examine how microgravity induces physiological changes in the microbes.
To Boldly Go: America's Next Era in Space. Sustaining Life on the Earth
Dr. France Cordova, NASA's Chief Scientist, opened this, the sixth seminar in the Administrator's Seminar Series, by introducing NASA Administrator Daniel S. Goldin. Mr Goldin welcomed the attendees and set the stage for Dr. Cordova's introduction of the first speaker, Dr. Robert Kates of Brown University. Dr. Kates primary concerns are global environmental changes, world hunger, and the size of the population. Human changes, he said, rival the changes of nature. Changes in the size of world population affect the need for more agricultural products, therefore more land for growing food, which leads to deforestation, which affects rainfall, and therefore the water supply which is in increased demand. Human ingenuity can reduce some shortages but generally doesn't keep up with increased demand for life-sustaining essentials. These problems require the concern of intergovernmental organizations, treaties and activities, as well as transnational corporations, and non-governmental and private, volunteer organizations. Next Dr. Diana Liverman of Pennsylvania State University spoke on human interactions regarding climate and society. She considered the effect of changes in land use on climate, using Mexico as an example. Mexicans changed from raising much wheat to raising more fruits and vegetables. This was in response to the demands of the market. The results were more industry, population growth, greater income, drought (because the new crops required more water), and conflicts over water supplies. Dr. Charles Kennel of the Office of Mission to Planet Earth joined Dr.s Cordova, Kates, and Liverman for the question and answer session that followed.
The D614G mutation in Spike: increased infectivity and neutralizing Ab sensitivity and the underlying mechanism [Slides]
Evidence is presented that there are now more SARS-CoV-2 viruses circulating in the human population globally that have the G614 form that was originally identified from the first human cases in Wuhan, China. Follow-up studies show that patients infected with G614 shed more viral nucleic avid compared with those with D614 and G614-bearing viruses show significantly higher infectious titers in vitro than their D614 counterparts.