While there is global warming in the lower atmosphere (below around 15 km altitude), the opposite is true in the upper atmosphere where carbon dioxide (CO 2 ) contributes to global cooling (Akmaev & Fomichev, 1998;Roble & Dickinson, 1989). CO 2 molecules gain energy by collisional excitation, notably with atomic oxygen (O), or by absorption of infrared (IR) radiation (Sharma & Roble, 2002). Energy can also be lost from excited CO 2 via collisions with other atmospheric molecules or via IR radiation emission at a wavelength of 15 μm. In the lower atmosphere this IR radiation is quickly reabsorbed leading to warming, but in the much thinner upper atmosphere, the radiation is lost to space or the lower atmosphere and leads to cooling. In the thermosphere (defined as 100-500 km altitude within this study), this cooling results in thermospheric contraction and a secular decrease in neutral density at any given altitude in the upper atmosphere (Laštovička et al., 2006).Solar activity also has a major impact on thermospheric neutral densities, and is often measured in either sunspot number or the F 10.7 radio emission index (Hathaway, 2015). Peaks within this cycle are associated
Emissions from transportation sources can impact local air quality and contribute to adverse health effects. The Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS), conducted over a 1-year period, researched emissions source characterization in the Argentine, Turner, and Armourdale, Kansas (KS) neighborhoods and the broader southeast Kansas City, KS area. This area is characterized as a near-source environment with impacts from large railyard operations, major roadways, and commercial and industrial facilities. The spatial and meteorological effects of particulate matter less than 2.5 µm (PM2.5), and black carbon (BC) pollutants on potential population exposures were evaluated at multiple sites using a combination of regulatory grade methods and instrumentation, low-cost sensors, citizen science, and mobile monitoring. The initial analysis of a subset of these data showed that mean reference grade PM2.5 concentrations (gravimetric) across all sites ranged from 7.92 to 9.34 µg/m3. Mean PM2.5 concentrations from low-cost sensors ranged from 3.30 to 5.94 µg/m3 (raw, uncorrected data). Pollution wind rose plots suggest that the sites are impacted by higher PM2.5 and BC concentrations when the winds originate near known source locations. Initial data analysis indicated that the observed PM2.5 and BC concentrations are driven by multiple air pollutant sources and meteorological effects. The KC-TRAQS overview and preliminary data analysis presented will provide a framework for forthcoming papers that will further characterize emission source attributions and estimate near-source exposures. This information will ultimately inform and clarify the extent and impact of air pollutants in the Kansas City area.
Introduction BackgroundAccurately propagating satellite orbits requires knowledge of the forces acting on the satellite. For satellites in low Earth orbit (less than 1,000 km), forces include terrestrial gravity, solar radiation pressure, lunar and solar gravity and drag caused by the atmosphere (Eshagh & Najafi Alamdari, 2007). The drag force increases dramatically as a satellite's altitude decreases and becomes significant below approximately 600 km (Fortescue et al., 2011). However, there are large uncertainties in modeling the magnitude of the drag acting on a satellite. To do so requires an understanding of the thermospheric mass density, winds and the satellite's ballistic coefficient. The largest contribution to error in the forecasting of satellite positions is specification of thermospheric density (Mehta et al., 2018), although for tumbling or complex geometries, the errors in the ballistic coefficient can be a substantial contribution.Currently a variety of mathematical models are used to provide estimates of the density. Empirical models are often used by satellite operators. They are fitted to measurements of thermospheric parameters; however such measurements are sparse. In particular, there are very few measurements between 100 and 250 km because balloons cannot reach these heights and satellites re-enter too quickly for any long term study. Fabry-Perot Interferometers can be used to measure wind between 220 and 600 km (Titheridge, 1995) and meteor radars can measure wind, as well as temperature and pressure, between 80 and 100 km (John et al., 2011;Reid et al., 2018).Physics-based models solve the equations which describe the physical processes in the thermosphere. Initially the atmospheric density, wind and temperatures are generally provided by empirical models, but a "spin-up" time is used for the results to stabilize. The spin-up time can be reduced in subsequent model runs by using previous output from the model. Neutral and ion species production is then calculated via chemical reaction equations and using solar X-rays and EUV conditions. Ion transportation and recombination are also considered. The initial and boundary conditions, as well as proxies for solar activity, are the main drivers for the models. There are a number of approaches to modeling the physics of the thermosphere, which rely on different numerical methods
Multi-model ensembles (MMEs) are used to improve the forecasts of thermospheric neutral densities. A variety of algorithms for constructing the model weights for the MMEs have been implemented including performance weighting, independence weighting and non-negative least squares. Using both empirical and physics-based models, compared against in-situ CHAMP observations, the skill of each MME weighting approach has been tested in both solar minimum and maximum conditions. In both cases the MME performs better than any individual model. A non-negative least squares weighting for the MME on a set of bias corrected models provides a 68% and 50% reduction in the mean square error compared to the best model (Jacchia-Bowman 2008) in the solar minimum and maximum cases respectively.
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