The expansion of satellite constellation applications brings attention to the need for responsive, reliable satellite communication. For preflight technology assessment of missions, a simulation of two spacecraft in low Earth orbit has been created to estimate clock synchronization and precision orbit determination based on measured instrumentation performance. A novel MATLAB-based numerical simulator was developed to model spacecraft-to-spacecraft laser time-transfer and estimate the offset between the spacecraft clocks over time. This simulation includes timing errors associated with laser pulse detection, as well as non-Gaussian clock drift models. Two on-board clocks are modeled: a cesium-based chip-scale atomic clock and a rubidium-based miniature atomic clock. The positions and velocities of the spacecraft at a reference epoch and the constant coefficients of a polynomial clock model are estimated. Results compare the estimated clock model of a mission operation that only uses GPS measurements and one that uses both GPS and laser pulse time-of-flight measurements between spacecraft referenced to their on-board clocks. Including lasing measurements reduces the root-mean-square clock model error to approximately 80% of the RMS of the cases with only GPS measurements. This simulation tool can be used to optimize the lasing operations schedule based on mission timing performance objectives.

Satellite constellations are growing in size and in utility for applications as diverse as providing reliable, low-latency internet service to rural areas and Earth science missions. This expansion of satellite constellations brings attention to the need for responsive and reliable satellite communication. Current research focuses on using pulsed laser communications as the method of relaying time signals instead of the radio frequency (RF). The upcoming CLICK (CubeSat Laser Infrared CrosslinK) missions (Massachusetts Institute of Technology, University of Florida, NASA Ames Research Center) [1] will demonstrate a space-craft-to-spacecraft laser communication link and time-transfer. For pre-flight technology assessment of missions such as CLICK, a simulation of a spacecraft constellation in Earth orbit has been created to estimate clock synchronization and precision orbit determination based on measured instrumentation performance. We have developed a novel MATLAB-based numerical simulator to model spacecraft-to-spacecraft laser time-transfer and estimate the offset between the spacecraft clocks over time. This simulation includes timing errors associated with laser pulse generation and detection, as well as non-Gaussian clock drift models. The two on-board clocks modeled are a cesium-based Chip-Scale Atomic Clock (CSAC) and a rubidium-based Miniature Atomic Clock (MAC), both produced by Microchip [2][3]. An example case of two spacecraft in a circular, low-Earth orbit receiving GPS position, GPS timing, and laser pulse timeof-flight measurements is simulated. The positions and velocities of the two spacecraft at a reference epoch and the constant clock model coefficients are estimated. Polynomial models of different orders were used as clock models. The effect of clock model order on the root-mean-square (RMS) of the clock error is apparent in the case using GPS and lasing measurements, showing that the clock model improves with increasing clock model order. Results compare the estimated clock model of a mission operation that only uses GPS measurements and a mission operation that uses both GPS and laser pulse time-of-flight measurements between spacecraft referenced to their on-board CSACs. Including lasing measurements reduces the RMS clock model error to approximately half the RMS of the cases with only GPS measurements. This simulation tool can be used to optimize the lasing operations schedule based on mission timing performance objectives.

This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Environmental Science. Please check back later for the full article. The volume of municipal solid waste produced in the United States has increased by 68% since 1980, up from 151 million to over 254 million tons per year. As the output of municipal waste has grown, more attention has been placed on the occupations associated with waste management. In 2014, the occupation of refuse and recyclable material collection was ranked as the 6th most dangerous job in the United States, with a rate of 27.1 deaths per 100,000 workers. With the revelation of reported exposure statistics among solid waste workers in the United States, the problem of the identification and assessment of occupational health risks among solid waste workers is receiving more consideration. From the generation of waste to its disposal, solid waste workers are exposed to substantial levels of physical, chemical, and biological toxins. Current waste management systems in the United States involve significant risk of contact with waste hazards, highlighting that prevention methods such as monitoring exposures, personal protection, engineering controls, job education and training, and other interventions are under-utilized. To recognize and address occupational hazards encountered by solid waste workers, it is necessary to discern potential safety concerns and their causes, as well as their direct and/or indirect impacts on the various types of workers. In solid waste management, the major industries processing solid waste are introduced as recycling, incineration, landfill, and composting. Thus, the reported exposures and potential occupational health risks need to be identified for workers in each of the aforementioned industries. Then, by acquiring data on reported exposure among solid waste workers, multiple county-level and state-level quantitative assessments for major occupational risks can be conducted using statistical assessment methods. To assess health risks among solid waste workers, the following questions must be answered: How can the methods of solid waste management be categorized? Which are the predominant occupational health risks among solid waste workers, and how can they be identified? Which practical and robust assessment methods are useful for evaluating occupational health risks among solid waste workers? What are possible solutions that can be implemented to reduce the occupational health hazard rates among solid waste workers?