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.

On-going efforts to understand the dynamics of coupled social-ecological (or more broadly, coupled infrastructure) systems and common pool resources have led to the generation of numerous datasets based on a large number of case studies. This data has facilitated the identification of important factors and fundamental principles which increase our understanding of such complex systems. However, the data at our disposal are often not easily comparable, have limited scope and scale, and are based on disparate underlying frameworks inhibiting synthesis, meta-analysis, and the validation of findings. Research efforts are further hampered when case inclusion criteria, variable definitions, coding schema, and inter-coder reliability testing are not made explicit in the presentation of research and shared among the research community. This paper first outlines challenges experienced by researchers engaged in a large-scale coding project; then highlights valuable lessons learned; and finally discusses opportunities for further research on comparative case study analysis focusing on social-ecological systems and common pool resources. Includes supplemental materials and appendices published in the International Journal of the Commons 2016 Special Issue. Volume 10 - Issue 2 - 2016.

Governing common pool resources (CPR) in the face of disturbances such as globalization and climate change is challenging. The outcome of any CPR governance regime is the influenced by local combinations of social, institutional, and biophysical factors, as well as cross-scale interdependencies. In this study, we take a step towards understanding multiple-causation of CPR outcomes by analyzing 1) the co-occurrence of Design Principles (DP) by activity (irrigation, fishery and forestry), and 2) the combination(s) of DPs leading to social and ecological success. We analyzed 69 cases pertaining to three different activities: irrigation, fishery, and forestry. We find that the importance of the design principles is dependent upon the natural and hard human made infrastructure (i.e. canals, equipment, vessels etc.). For example, clearly defined social boundaries are important when the natural infrastructure is highly mobile (i.e. tuna fish), while monitoring is more important when the natural infrastructure is more static (i.e. forests or water contained within an irrigation system). However, we also find that congruence between local conditions and rules and proportionality between investment and extraction are key for CPR success independent from the natural and human hard made infrastructure. We further provide new visualization techniques for co-occurrence patterns and add to qualitative comparative analysis by introducing a reliability metric to deal with a large meta-analysis dataset on secondary data where information is missing or uncertain.

Includes supplemental materials and appendices publications in International Journal of the Commons 2016 Special Issue. Volume 10 - Issue 2 - 2016

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.

Faced with numerous seemingly intractable social and environmental challenges, many scholars and practitioners are increasingly interested in understanding how to actively engage and transform the existing systems holding such problems in place. Although a variety of analytical models have emerged in recent years, most emphasize either the social or ecological elements of such transformations rather than their coupled nature. To address this, first we have presented a definition of the core elements of a social-ecological system (SES) that could potentially be altered in a transformation. Second, we drew on insights about transformation from three branches of literature focused on radical change, i.e., social movements, socio-technical transitions, and social innovation, and gave consideration to the similarities and differences with the current studies by resilience scholars. Drawing on these findings, we have proposed a framework that outlines the process and phases of transformative change in an SES. Future research will be able to utilize the framework as a tool for analyzing the alteration of social-ecological feedbacks, identifying critical barriers and leverage points and assessing the outcome of social-ecological transformations.

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.

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.