ASU Scholarship Showcase

Urban environments are the primary contributors to global anthropogenic carbon emissions. Because much of the growth in CO₂ emissions will originate from cities, there is a need to develop, assess, and improve measurement and modeling strategies for quantifying and monitoring greenhouse gas emissions from large urban centers. In this study the uncertainties in an aircraft-based mass balance approach for quantifying carbon dioxide and methane emissions from an urban environment, focusing on Indianapolis, IN, USA, are described. The relatively level terrain of Indianapolis facilitated the application of mean wind fields in the mass balance approach. We investigate the uncertainties in our aircraft-based mass balance approach by (1) assessing the sensitivity of the measured flux to important measurement and analysis parameters including wind speed, background CO₂ and CH₄, boundary layer depth, and interpolation technique, and (2) determining the flux at two or more downwind distances from a point or area source (with relatively large source strengths such as solid waste facilities and a power generating station) in rapid succession, assuming that the emission flux is constant. When we quantify the precision in the approach by comparing the estimated emissions derived from measurements at two or more downwind distances from an area or point source, we find that the minimum and maximum repeatability were 12 and 52%, with an average of 31%. We suggest that improvements in the experimental design can be achieved by careful determination of the background concentration, monitoring the evolution of the boundary layer through the measurement period, and increasing the number of downwind horizontal transect measurements at multiple altitudes within the boundary layer.

Large urban emissions of greenhouse gases result in large atmospheric enhancements relative to background that are easily measured. Using CO₂ mole fractions and Δ¹⁴C and δ¹³C values of CO₂ in the Los Angeles megacity observed in inland Pasadena (2006–2013) and coastal Palos Verdes peninsula (autumn 2009–2013), we have determined time series for CO₂ contributions from fossil fuel combustion (C_ff) for both sites and broken those down into contributions from petroleum and/or gasoline and natural gas burning for Pasadena. We find a 10 % reduction in Pasadena C_ff during the Great Recession of 2008–2010, which is consistent with the bottom-up inventory determined by the California Air Resources Board. The isotopic variations and total atmospheric CO₂ from our observations are used to infer seasonality of natural gas and petroleum combustion. The trend of CO₂ contributions to the atmosphere from natural gas combustion is out of phase with the seasonal cycle of total natural gas combustion seasonal patterns in bottom-up inventories but is consistent with the seasonality of natural gas usage by the area's electricity generating power plants. For petroleum, the inferred seasonality of CO₂ contributions from burning petroleum is delayed by several months relative to usage indicated by statewide gasoline taxes. Using the high-resolution Hestia-LA data product to compare C_ff from parts of the basin sampled by winds at different times of year, we find that variations in observed fossil fuel CO₂ reflect seasonal variations in wind direction. The seasonality of the local CO₂ excess from fossil fuel combustion along the coast, on Palos Verdes peninsula, is higher in autumn and winter than spring and summer, almost completely out of phase with that from Pasadena, also because of the annual variations of winds in the region. Variations in fossil fuel CO₂ signals are consistent with sampling the bottom-up Hestia-LA fossil CO₂ emissions product for sub-city source regions in the LA megacity domain when wind directions are considered.

Recent advances in fossil fuel CO₂ (FFCO₂) emission inventories enable sensitivity tests of simulated atmospheric CO₂ concentrations to sub-annual variations in FFCO₂ emissions and what this implies for the interpretation of observed CO₂. Six experiments are conducted to investigate the potential impact of three cycles of FFCO₂ emission variability (diurnal, weekly and monthly) using a global tracer transport model. Results show an annual FFCO₂ rectification varying from −1.35 to +0.13 ppm from the combination of all three cycles. This rectification is driven by a large negative diurnal FFCO₂ rectification due to the covariation of diurnal FFCO₂ emissions and diurnal vertical mixing, as well as a smaller positive seasonal FFCO₂ rectification driven by the covariation of monthly FFCO₂ emissions and monthly atmospheric transport. The diurnal FFCO₂ emissions are responsible for a diurnal FFCO₂ concentration amplitude of up to 9.12 ppm at the grid cell scale. Similarly, the monthly FFCO₂ emissions are responsible for a simulated seasonal CO₂ amplitude of up to 6.11 ppm at the grid cell scale. The impact of the diurnal FFCO₂ emissions, when only sampled in the local afternoon, is also important, causing an increase of +1.13 ppmv at the grid cell scale. The simulated CO₂ concentration impacts from the diurnally and seasonally varying FFCO₂ emissions are centered over large source regions in the Northern Hemisphere, extending to downwind regions. This study demonstrates the influence of sub-annual variations in FFCO₂ emissions on simulated CO₂ concentration and suggests that inversion studies must take account of these variations in the affected regions.

Background: Studies show that ex-prisoners often experience more health problems than the general population; unfortunately, these issues follow them upon their release from prison. As such, it is possible re-entry rates signal the need for neighborhood-based health care organizations (HCOs). We ask: are incarceration and re-entry rates associated with the availability of HCOs?

Methods: Using 2008 Central Business Pattern data, 2008 prison admissions and release data, and 2000 and 2010 census data, we test whether prison admission and release rates impact the availability of HCOs net of neighborhood characteristics in Arkansas using Logit-Poisson hurdle models with county fixed effects.

Results: We find that the incarceration and re-entry rates – together known as coercive mobility -- are related to whether a neighborhood has one or more HCOs, but not to the number of HCOs in a neighborhood.

Conclusion: Future public policies should aim to locate health care organizations in areas where there is significant churning of individuals in and out of prison.

Objective: To estimate the effects on homicide rates of the gang truce that was brokered in El Salvador in 2012.

Methods: Mathematical models based on municipal-level census, crime and gang-intelligence data were used to estimate the effect of the truce on homicide rates. One model estimated the overall effect after accounting for the linear trend and seasonality in the homicide rate. In a moderated-effect model, we investigated the relationship between the truce effect and the numbers of MS13 (Mara Salvatrucha 13) and Eighteenth-Street gang members imprisoned per 100 000 population. We then ran each of these two models with additional control variables. We compared values before the truce – 1 January 2010 to 29 February 2012 – with those after the truce – 1 March 2012 to 31 December 2013.

Findings: The overall-effect models with and without additional control variables indicated a homicide rate after the truce that was significantly lower than the value before the truce, giving rate ratios of 0.55 (95% confidence interval, CI: 0.49–0.63) and 0.61 (95% CI: 0.54–0.69), respectively. For any given municipality, the effectiveness of the truce appeared to increase as the number of MS13 gang members imprisoned per 100 000 population increased. We did not observe the same significant relationship for imprisoned Eighteenth-Street gang members.

Conclusion: In the 22 months following the establishment of a national gang truce, the homicide rate was about 40% lower than in the preceding 26 months. The truce’s impact appeared particularly strong in municipalities with relatively high numbers of imprisoned MS13 gang members per 100 000 population.

Background: Extreme heat is a leading weather-related cause of mortality in the United States, but little guidance is available regarding how temperature variable selection impacts heat–mortality relationships.
Objectives: We examined how the strength of the relationship between daily heat-related mortality and temperature varies as a function of temperature observation time, lag, and calculation method.
Methods: Long time series of daily mortality counts and hourly temperature for seven U.S. cities with different climates were examined using a generalized additive model. The temperature effect was modeled separately for each hour of the day (with up to 3-day lags) along with different methods of calculating daily maximum, minimum, and mean temperature. We estimated the temperature effect on mortality for each variable by comparing the 99th versus 85th temperature percentiles, as determined from the annual time series.

Results: In three northern cities (Boston, MA; Philadelphia, PA; and Seattle, WA) that appeared to have the greatest sensitivity to heat, hourly estimates were consistent with a diurnal pattern in the heat-mortality response, with strongest associations for afternoon or maximum temperature at lag 0 (day of death) or afternoon and evening of lag 1 (day before death). In warmer, southern cities, stronger associations were found with morning temperatures, but overall the relationships were weaker. The strongest temperature–mortality relationships were associated with maximum temperature, although mean temperature results were comparable.

Conclusions: There were systematic and substantial differences in the association between temperature and mortality based on the time and type of temperature observation. Because the strongest hourly temperature–mortality relationships were not always found at times typically associated with daily maximum temperatures, temperature variables should be selected independently for each study location. In general, heat-mortality was more closely coupled to afternoon and maximum temperatures in most cities we examined, particularly those typically prone to heat-related mortality.

Background: Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events.

Objectives: This quantitative study was designed to link temperature with mortality and morbidity events in Maricopa County, Arizona, USA, with a focus on the summer season.
Methods: Using Poisson regression models that controlled for temporal confounders, we assessed daily temperature–health associations for a suite of mortality and morbidity events, diagnoses, and temperature metrics. Minimum risk temperatures, increasing risk temperatures, and excess risk temperatures were statistically identified to represent different “trigger points” at which heat-health intervention measures might be activated.

Results: We found significant and consistent associations of high environmental temperature with all-cause mortality, cardiovascular mortality, heat-related mortality, and mortality resulting from conditions that are consequences of heat and dehydration. Hospitalizations and emergency department visits due to heat-related conditions and conditions associated with consequences of heat and dehydration were also strongly associated with high temperatures, and there were several times more of those events than there were deaths. For each temperature metric, we observed large contrasts in trigger points (up to 22°C) across multiple health events and diagnoses.

Conclusion: Consideration of multiple health events and diagnoses together with a comprehensive approach to identifying threshold temperatures revealed large differences in trigger points for possible interventions related to heat. Providing an array of heat trigger points applicable for different end-users may improve the public health response to a problem that is projected to worsen in the coming decades.

Megacities are major sources of anthropogenic fossil fuel CO₂(FFCO₂) emissions. The spatial extents of these large urban systems cover areas of 10 000 km² or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO₂ emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO₂ emission product, Hestia-LA, to simulate atmospheric CO₂ concentrations across the LA megacity at spatial resolutions as fine as  ∼  1 km. We evaluated multiple WRF configurations, selecting one that minimized errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO₂ emission products to evaluate the impact of the spatial resolution of the CO₂ emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO₂ concentrations. We find that high spatial resolution in the fossil fuel CO₂ emissions is more important than in the atmospheric model to capture CO₂ concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO₂ fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO₂ fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO₂ concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO₂ emissions monitoring in the LA megacity requires FFCO₂ emissions modelling with  ∼1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.

The (110) plane of Co₃O₄ spinel exhibits significantly higher rates of carbon monoxide conversion due to the presence of active Co³⁺ species at the surface. However, experimental studies of Co₃O₄ (110) surfaces and interfaces have been limited by the difficulties in growing high-quality films. We report thin (10–250 Å) Co₃O₄ films grown by molecular beam epitaxy in the polar (110) direction on MgAl₂O₄ substrates. Reflection high-energy electron diffraction, atomic force microscopy, x-ray diffraction, and transmission electron microscopy measurements attest to the high quality of the as-grown films. Furthermore, we investigate the electronic structure of this material by core level and valence band x-ray photoelectron spectroscopy, and first-principles density functional theory calculations. Ellipsometry reveals a direct band gap of 0.75 eV and other interband transitions at higher energies. A valence band offset of 3.2 eV is measured for the Co₃O₄/MgAl₂O₄ heterostructure. Magnetic measurements show the signature of antiferromagnetic ordering at 49 K. FTIR ellipsometry finds three infrared-active phonons between 300 and 700 cm^-1.

Zintl phases are a class of intermetallic materials that have simultaneously ionic and covalent bonding resulting from charge transfer between two different atomic species. We present a combined first principles and experimental study of Zintl-phase SrAl4, which is grown in thin film form on the perovskite oxide LaAlO3 using molecular beam epitaxy. The structural properties are investigated using reflection-high-energy electron diffraction, x-ray diffraction, and cross-section transmission electron microscopy, which reveal relaxed epitaxial island growth. Photoelectron spectroscopy measurements verify the Zintl-Klemm nature of the bonding in the material and are utilized to determine the band offset and the work function of SrAl4, while transport measurements confirm its metallic behavior. The experimentally observed properties are confirmed using density functional calculations.