ASU Scholarship Showcase

High-resolution, global quantification of fossil fuel CO[subscript 2] emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high-resolution fossil fuel CO[subscript 2] emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long-term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long-term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter-term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO[subscript 2] emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO[subscript 2] emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set.

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.

Atmospheric CO₂ inversions estimate surface carbon fluxes from an optimal fit to atmospheric CO₂ measurements, usually including prior constraints on the flux estimates. Eleven sets of carbon flux estimates are compared, generated by different inversions systems that vary in their inversions methods, choice of atmospheric data, transport model and prior information. The inversions were run for at least 5 yr in the period between 1990 and 2010. Mean fluxes for 2001–2004, seasonal cycles, interannual variability and trends are compared for the tropics and northern and southern extra-tropics, and separately for land and ocean. Some continental/basin-scale subdivisions are also considered where the atmospheric network is denser. Four-year mean fluxes are reasonably consistent across inversions at global/latitudinal scale, with a large total (land plus ocean) carbon uptake in the north (−3.4 Pg C yr^-1 (±0.5 Pg C yr^-1 standard deviation), with slightly more uptake over land than over ocean), a significant although more variable source over the tropics (1.6 ± 0.9 Pg C yr^-1) and a compensatory sink of similar magnitude in the south (−1.4 ± 0.5 Pg C yr^-1) corresponding mainly to an ocean sink. Largest differences across inversions occur in the balance between tropical land sources and southern land sinks. Interannual variability (IAV) in carbon fluxes is larger for land than ocean regions (standard deviation around 1.06 versus 0.33 Pg C yr[superscript −1] for the 1996–2007 period), with much higher consistency among the inversions for the land. While the tropical land explains most of the IAV (standard deviation ~ 0.65 Pg C yr^-1), the northern and southern land also contribute (standard deviation ~ 0.39 Pg C yr^-1). Most inversions tend to indicate an increase of the northern land carbon uptake from late 1990s to 2008 (around 0.1 Pg C yr^-1, predominantly in North Asia. The mean seasonal cycle appears to be well constrained by the atmospheric data over the northern land (at the continental scale), but still highly dependent on the prior flux seasonality over the ocean. Finally we provide recommendations to interpret the regional fluxes, along with the uncertainty estimates.

This paper presents an analysis of methane emissions from the Los Angeles Basin at monthly timescales across a 4-year time period – from September 2011 to August 2015. Using observations acquired by a ground-based near-infrared remote sensing instrument on Mount Wilson, California, combined with atmospheric CH₄–CO₂ tracer–tracer correlations, we observed −18 to +22 % monthly variability in CH₄ : CO₂ from the annual mean in the Los Angeles Basin. Top-down estimates of methane emissions for the basin also exhibit significant monthly variability (−19 to +31 % from annual mean and a maximum month-to-month change of 47 %). During this period, methane emissions consistently peaked in the late summer/early fall and winter. The estimated annual methane emissions did not show a statistically significant trend over the 2011 to 2015 time period.

Quiescin sulfhydryl oxidase 1 (QSOX1) is a highly conserved disulfide bond-generating enzyme that is overexpressed in diverse tumor types. Its enzymatic activity promotes the growth and invasion of tumor cells and alters extracellular matrix composition. In a nude mouse-human tumor xenograft model, tumors containing shRNA for QSOX1 grew significantly more slowly than controls, suggesting that QSOX1 supports a proliferative phenotype in vivo. High throughput screening experiments identified ebselen as an in vitro inhibitor of QSOX1 enzymatic activity. Ebselen treatment of pancreatic and renal cancer cell lines stalled tumor growth and inhibited invasion through Matrigel in vitro. Daily oral treatment with ebselen resulted in a 58% reduction in tumor growth in mice bearing human pancreatic tumor xenografts compared to controls. Mass spectrometric analysis of ebselen-treated QSOX1 mechanistically revealed that C165 and C237 of QSOX1 covalently bound to ebselen. This report details the anti-neoplastic properties of ebselen in pancreatic and renal cancer cell lines. The results here offer a “proof-of-principle” that enzymatic inhibition of QSOX1 may have clinical relevancy.

Chronic manganese (Mn) exposure is associated with neuromotor and neurocognitive deficits, but the exact mechanism of Mn neurotoxicity is still unclear. With the advent of magnetic resonance imaging (MRI), in-vivo analysis of brain structures has become possible. Among different sub-cortical structures, the basal ganglia (BG) has been investigated as a putative anatomical biomarker in MR-based studies of Mn toxicity. However, previous investigations have yielded inconsistent results in terms of regional MR signal intensity changes. These discrepancies may be due to the subtlety of brain alterations caused by Mn toxicity, coupled to analysis techniques that lack the requisite detection power. Here, based on brain MRI, we apply a 3D surface-based morphometry method on 3 bilateral basal ganglia structures in school-age children chronically exposed to Mn through drinking water to investigate the effect of Mn exposure on brain anatomy. Our method successfully pinpointed significant enlargement of many areas of the basal ganglia structures, preferentially affecting the putamen. Moreover, these areas showed significant correlations with fine motor performance, indicating a possible link between altered basal ganglia neurodevelopment and declined motor performance in high Mn exposed children.

S-cysteinylated albumin and methionine-oxidized apolipoprotein A-I (apoA-I) have been posed as candidate markers of diseases associated with oxidative stress. Here, a dilute-and-shoot form of LC–electrospray ionization–MS requiring half a microliter of blood plasma was employed to simultaneously quantify the relative abundance of these oxidized proteoforms in samples stored at −80 °C, −20 °C, and room temperature and exposed to multiple freeze-thaw cycles and other adverse conditions in order to assess the possibility that protein oxidation may occur as a result of poor sample storage or handling. Samples from a healthy donor and a participant with poorly controlled type 2 diabetes started at the same low level of protein oxidation and behaved similarly; significant increases in albumin oxidation via S-cysteinylation were found to occur within hours at room temperature and days at −20 °C. Methionine oxidation of apoA-I took place on a longer time scale, setting in after albumin oxidation reached a plateau. Freeze–thaw cycles had a minimal effect on protein oxidation. In matched collections, protein oxidation in serum was the same as that in plasma. Albumin and apoA-I oxidation were not affected by sample headspace or the degree to which vials were sealed. ApoA-I, however, was unexpectedly found to oxidize faster in samples with lower surface-area-to-volume ratios. An initial survey of samples from patients with inflammatory conditions normally associated with elevated oxidative stress-including acute myocardial infarction and prostate cancer—demonstrated a lack of detectable apoA-I oxidation. Albumin S-cysteinylation in these samples was consistent with known but relatively brief exposures to temperatures above −30 °C (the freezing point of blood plasma). Given their properties and ease of analysis, these oxidized proteoforms, once fully validated, may represent the first markers of blood plasma specimen integrity based on direct measurement of oxidative molecular damage that can occur under suboptimal storage conditions.

The apolipoprotein E (APOE) e4 allele is the most prevalent genetic risk factor for Alzheimer's disease (AD). Hippocampal volumes are generally smaller in AD patients carrying the e4 allele compared to e4 noncarriers. Here we examined the effect of APOE e4 on hippocampal morphometry in a large imaging database—the Alzheimer's Disease Neuroimaging Initiative (ADNI). We automatically segmented and constructed hippocampal surfaces from the baseline MR images of 725 subjects with known APOE genotype information including 167 with AD, 354 with mild cognitive impairment (MCI), and 204 normal controls. High-order correspondences between hippocampal surfaces were enforced across subjects with a novel inverse consistent surface fluid registration method. Multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance were computed for surface deformation analysis. Using Hotelling's T2 test, we found significant morphological deformation in APOE e4 carriers relative to noncarriers in the entire cohort as well as in the nondemented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes. Our findings are consistent with previous studies that showed e4 carriers exhibit accelerated hippocampal atrophy; we extend these findings to a novel measure of hippocampal morphometry. Hippocampal morphometry has significant potential as an imaging biomarker of early stage AD.

Attributing observed CO2 variations to human or natural cause is critical to deducing and tracking emissions from observations. We have used in situ CO2, CO, and planetary boundary layer height (PBLH) measurements recorded during the CalNex-LA (CARB et al., 2008) ground campaign of 15 May-15 June 2010, in Pasadena, CA, to deduce the diurnally varying anthropogenic component of observed CO2 in the megacity of Los Angeles (LA). This affordable and simple technique, validated by carbon isotope observations and WRF-STILT (Weather Research and Forecasting model - Stochastic Time-Inverted Lagrangian Transport model) predictions, is shown to robustly attribute observed CO2 variation to anthropogenic or biogenic origin over the entire diurnal cycle. During CalNex-LA, local fossil fuel combustion contributed up to similar to 50% of the observed CO2 enhancement overnight, and similar to 100% of the enhancement near midday. This suggests that sufficiently accurate total column CO2 observations recorded near midday, such as those from the GOSAT or OCO-2 satellites, can potentially be used to track anthropogenic emissions from the LA megacity.

The apolipoprotein E (APOE) e4 genotype is a powerful risk factor for late-onset Alzheimer’s disease (AD). In the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort, we previously reported significant baseline structural differences in APOE e4 carriers relative to non-carriers, involving the left hippocampus more than the right—a difference more pronounced in e4 homozygotes than heterozygotes. We now examine the longitudinal effects of APOE genotype on hippocampal morphometry at 6-, 12- and 24-months, in the ADNI cohort. We employed a new automated surface registration system based on conformal geometry and tensor-based morphometry. Among different hippocampal surfaces, we computed high-order correspondences, using a novel inverse-consistent surface-based fluid registration method and multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance. At each time point, using Hotelling’s T² test, we found significant morphological deformation in APOE e4 carriers relative to non-carriers in the full cohort as well as in the non-demented (pooled MCI and control) subjects at each follow-up interval. In the complete ADNI cohort, we found greater atrophy of the left hippocampus than the right, and this asymmetry was more pronounced in e4 homozygotes than heterozygotes. These findings, combined with our earlier investigations, demonstrate an e4 dose effect on accelerated hippocampal atrophy, and support the enrichment of prevention trial cohorts with e4 carriers.