With the increase in the severity of drought conditions in the Southwest region of the U.S. paired with rising temperatures, it is becoming increasingly important to look at the systems used to keep people cool in hot-arid cities like Tempe, Arizona. Outdoor misting systems are often deployed by businesses. These systems rely on the evaporative cooling effect of water. This study examines the relationship between misting droplet size, water usage, and thermal comfort using low-pressure misting systems, tested within hot and dry conditions representative of the arid U.S. southwest. A model misting system using three nozzle orifice sizes was set up in a controlled heat chamber environment (starting baseline conditions of 40°C air temperature and 15 % relative humidity). Droplet size was measured using water-reactive paper, while water use was determined based on weight-change measurements. These measurements were paired with temperature and humidity measurements observed in several locations around the chamber to allow for a spatial analysis. Thermal comfort is determined based on psychrometric changes (temperature and absolute humidity) within the room. On average, air temperatures decreased between 2 to 4°C depending on nozzle size and sensor location. The 0.4 mm nozzle had a decent spread across the heat chamber and balanced water usage and effectiveness well. Limitations within the study showed ventilation is important for an effective system, corroborating other studies findings and suggesting that adding air circulation could improve evaporation and comfort and thus effectiveness. Finally, visual cues, such as wetted surfaces, can signal businesses to change nozzle sizes and/or make additional modifications to the system area.
technological systems that affect society, such as communication infrastructures. Data
assimilation addresses the challenge of state specification by incorporating system
observations into the model estimates. In this research, a particular data
assimilation technique called the Local Ensemble Transform Kalman Filter (LETKF) is
applied to the ionosphere, which is a domain of practical interest due to its effects
on infrastructures that depend on satellite communication and remote sensing. This
dissertation consists of three main studies that propose strategies to improve space-
weather specification during ionospheric extreme events, but are generally applicable
to Earth-system models:
Topic I applies the LETKF to estimate ion density with an idealized model of
the ionosphere, given noisy synthetic observations of varying sparsity. Results show
that the LETKF yields accurate estimates of the ion density field and unobserved
components of neutral winds even when the observation density is spatially sparse
(2% of grid points) and there is large levels (40%) of Gaussian observation noise.
Topic II proposes a targeted observing strategy for data assimilation, which uses
the influence matrix diagnostic to target errors in chosen state variables. This
strategy is applied in observing system experiments, in which synthetic electron density
observations are assimilated with the LETKF into the Thermosphere-Ionosphere-
Electrodynamics Global Circulation Model (TIEGCM) during a geomagnetic storm.
Results show that assimilating targeted electron density observations yields on
average about 60%–80% reduction in electron density error within a 600 km radius of
the observed location, compared to 15% reduction obtained with randomly placed
vertical profiles.
Topic III proposes a methodology to account for systematic model bias arising
ifrom errors in parametrized solar and magnetospheric inputs. This strategy is ap-
plied with the TIEGCM during a geomagnetic storm, and is used to estimate the
spatiotemporal variations of bias in electron density predictions during the
transitionary phases of the geomagnetic storm. Results show that this strategy reduces
error in 1-hour predictions of electron density by about 35% and 30% in polar regions
during the main and relaxation phases of the geomagnetic storm, respectively.
Methods: Middle and high school adolescents (n=40; 50% female; 52.5% Hispanic) in the Phoenix, AZ area were asked to rank marketing materials (n=35) from favorite to least favorite in four categories: table tents, medium posters, large posters and announcements. Favorites were determined by showing participants two items at a time and having them choose which they preferred; items were displayed to each adolescent in a random order. Adolescents participated in a 20-30 minute interview on their favorite items in each category based on acceptance/attractiveness, comprehension, relevance, motivation and uniqueness of the materials. A content analysis was performed on top rated marketing materials. Top rated marketing materials were determined by the number of times the advertisement was ranked first in its category.
Results: An analysis of the design features of the items indicated that most participants (84%) preferred marketing materials with more than 4 color groups. Participant preference of advertisement length and word count was varied. A total of 5 themes and 20 subthemes emerged when participants discussed their favorite FV advertisements. Themes included: likes (e.g., colors, length, FV shown), dislikes (e.g., length, FV shown), health information (e.g., vitamin shown), comprehension (e.g., doesn’t recognize FV), and social aspects (e.g., peer opinion). Peer opinion often influenced participant opinion on marketing materials. Participants often said peers wouldn’t like the advertisements shown: “…kids my age think that vegetables are not good, and they like food more than vegetables.” Fruits and vegetable pictured as well as the information in the marketing materials also influenced adolescent preference.
Conclusion: Students preferred advertisements with more color and strong visual aspects. Word count had minimal influence on their opinions of the marketing materials, while information mentioned and peer opinion did have a positive effect. Further research needs to be done to determine if there is a link between adolescent preferences on FV marketing materials and FV consumption habits.
The first paper is based on a systematic literature review where evidence from morphological mitigation strategies in HUDs were critically reviewed, synthesized and integrated. Metrics, measurements, and methods were extracted to examine the applicability of the different strategies, and a content synthesis identified the levels of strategy success. Collective challenges and uncertainties were interpreted to compare aspirational goals from actualities of morphological mitigation strategies.
The second paper unpacks the relationship of urban morphological attributes in influencing thermal conditions to assess latent magnitudes of heat amelioration strategies. Mindful of the challenges presented in the first study, a 92-day summer field-measurement campaign captured system dynamics of urban thermal stimuli within sub-diurnal phenomena. A composite data set of sub-hourly air temperature measurements with sub-meter morphological attributes was built, statistically analyzed, and modeled. Morphological mediation effects were found to vary hourly with different patterns under varying weather conditions in non-linear associations. Results suggest mitigation interventions be investigated and later tested on a site- use and time-use basis.
The third paper concludes with a simulation-based study to conform on the collective findings of the earlier studies. The microclimate model ENVI-met 4.4, combined with field measurements, was used to simulate the effect of rooftop shade-sails in cooling the near ground thermal environment. Results showed significant cooling effects and thus presented a novel shading approach that challenges orthodox mitigation strategies in HUDs.
Lagrangian measures, identified with finite-time Lyapunov exponents, are first used to characterize transport patterns of inertial pollutant particles. Motivated by actual events the focus is on flows in realistic urban geometry. Both deterministic and stochastic transport patterns are identified, as inertial Lagrangian coherent structures. For the deterministic case, the organizing structures are well defined and are extracted at different hours of a day to reveal the variability of coherent patterns. For the stochastic case, a random displacement model for fluid particles is formulated, and used to derive the governing equations for inertial particles to examine the change in organizing structures due to ``zeroth-order'' random noise. It is found that, (1) the Langevin equation for inertial particles can be reduced to a random displacement model; (2) using random noise based on inhomogeneous turbulence, whose diffusivity is derived from $k$-$\epsilon$ models, major coherent structures survive to organize local flow patterns and weaker structures are smoothed out due to random motion.
A study of three-dimensional Lagrangian coherent structures (LCS) near HKIA is then presented and related to previous developments of two-dimensional (2D) LCS analyses in detecting windshear experienced by landing aircraft. The LCS are contrasted among three independent models and against 2D coherent Doppler light detection and ranging (LIDAR) data. Addition of the velocity information perpendicular to the lidar scanning cone helps solidify flow structures inferred from previous studies; contrast among models reveals the intramodel variability; and comparison with flight data evaluates the performance among models in terms of Lagrangian analyses. It is found that, while the three models and the LIDAR do recover similar features of the windshear experienced by a landing aircraft (along the landing trajectory), their Lagrangian signatures over the entire domain are quite different - a portion of each numerical model captures certain features resembling those LCS extracted from independent 2D LIDAR analyses based on observations. Overall, it was found that the Weather Research and Forecast (WRF) model provides the best agreement with the LIDAR data.
Finally, the three-dimensional variational (3DVAR) data assimilation scheme in WRF is used to incorporate the LIDAR line of sight velocity observations into the WRF model forecast at HKIA. Using two different days as test cases, it is found that the LIDAR data can be successfully and consistently assimilated into WRF. Using the updated model forecast LCS are extracted along the LIDAR scanning cone and compare to onboard flight data. It is found that the LCS generated from the updated WRF forecasts are generally better correlated with the windshear experienced by landing aircraft as compared to the LIDAR extracted LCS alone, which suggests that such a data assimilation scheme could be used for the prediction of windshear events.
Methods First-year students’ meal plan and residence information was provided by a large, public, southwestern university for the 2015-2016 academic year. A subset of students (n=619) self-reported their food security status. Logistic generalized estimating equations (GEEs) were used to determine if meal plan purchase and use were associated with food insecurity. Linear GEEs were used to examine several potential reasons for lower meal plan use. Logistic and Linear GEEs were used to determine similarities in meal plan purchase and use for a total of 599 roommate pairs (n=1186 students), and 557 floormates.
Results Students did not use all of the meals available to them; 7% of students did not use their meal plan for an entire month. After controlling for socioeconomic factors, compared to students on unlimited meal plans, students on the cheapest meal plan were more likely to report food insecurity (OR=2.2, 95% CI=1.2, 4.1). In Fall, 26% of students on unlimited meal plans reported food insecurity. Students on the 180 meals/semester meal plan who used fewer meals were more likely to report food insecurity (OR=0.9, 95% CI=0.8, 1.0); after gender stratification this was only evident for males. Students’ meal plan use was lower if the student worked a job (β=-1.3, 95% CI=-2.3, -0.3) and higher when their roommate used their meal plan frequently (β=0.09, 99% CI=0.04, 0.14). Roommates on the same meal plan (OR=1.56, 99% CI=1.28, 1.89) were more likely to use their meals together.
Discussion This study suggests that determining why students are not using their meal plan may be key to minimizing the prevalence of food insecurity on college campuses, and that strategic roommate assignments may result in students’ using their meal plan more frequently. Students’ meal plan information provides objective insights into students’ university transition.