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ASU Scholarship Showcase


This growing collection consists of scholarly works authored by ASU-affiliated faculty, students and community members, and contains many open access articles. ASU-affiliated authors are encouraged to Share Your Work in the ASU Digital Repository.


Contributor
Date Range
2013 2017


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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 ...

Contributors
Asefi-Najafabady, Salvi, Rayner, P. J., Gurney, Kevin, et al.
Created Date
2014-09-16

Urban environments are the primary contributors to global anthropogenic carbon emissions. Because much of the growth in CO[subscript 2] 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 ...

Contributors
Cambaliza, M. O. L., Shepson, P. B., Caulton, D. R., et al.
Created Date
2014-09-02

Atmospheric radiocarbon ([superscript 14]C) represents an important observational constraint on emissions of fossil-fuel derived carbon into the atmosphere due to the absence of [superscript 14]C in fossil fuel reservoirs. The high sensitivity and precision that accelerator mass spectrometry (AMS) affords in atmospheric [superscript 14]C analysis has greatly increased the potential for using such measurements to evaluate bottom-up emissions inventories of fossil fuel CO[subscript 2] (CO[subscript 2]ff), as well as those for other co-emitted species. Here we use observations of [superscript 14]CO[subscript 2] and a series of primary hydrocarbons and combustion tracers from discrete air samples collected between June 2009 and ...

Contributors
LaFranchi, B. W., Petron, G., Miller, J. B., et al.
Created Date
2013-11-15

A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current ...

Contributors
Ciais, P., Dolman, A. J., Bombelli, A., et al.
Created Date
2013-11-30

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 ...

Contributors
Newman, S., Jeong, S., Fischer, M.L., et al.
Created Date
2013-04-26

Atmospheric CO[subscript 2] inversions estimate surface carbon fluxes from an optimal fit to atmospheric CO[subscript 2] 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 ...

Contributors
Peylin, P., Law, R. M., Gurney, Kevin, et al.
Created Date
2013-10-24

Megacities are major sources of anthropogenic fossil fuel CO[subscript 2] (FFCO[subscript 2]) emissions. The spatial extents of these large urban systems cover areas of 10 000 km[superscript 2] or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO[subscript 2] emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO[subscript 2] emission product, Hestia-LA, to simulate atmospheric CO[subscript 2] concentrations across the LA megacity at spatial resolutions as fine as ∼ 1 km. We evaluated multiple WRF configurations, selecting one that ...

Contributors
Feng, Sha, Lauvaux, Thomas, Newman, Sally, et al.
Created Date
2016-07-22

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 CH[subscript 4]–CO[subscript 2] tracer–tracer correlations, we observed −18 to +22 % monthly variability in CH[subscript 4] : CO[subscript 2] 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 ...

Contributors
Wong, Clare K., Pongetti, Thomas J., Oda, Tom, et al.
Created Date
2016-10-26

Quantifying greenhouse gas (GHG) emissions from cities is a key challenge towards effective emissions management. An inversion analysis from the INdianapolis FLUX experiment (INFLUX) project, as the first of its kind, has achieved a top-down emission estimate for a single city using CO[subscript 2] data collected by the dense tower network deployed across the city. However, city-level emission data, used as a priori emissions, are also a key component in the atmospheric inversion framework. Currently, fine-grained emission inventories (EIs) able to resolve GHG city emissions at high spatial resolution, are only available for few major cities across the globe. Following ...

Contributors
Oda, Tomohiro, Lauvaux, Thomas, Lu, Dengsheng, et al.
Created Date
2017-06-14

The ‘Hestia Project’ uses a bottom-up approach to quantify fossil fuel CO[subscript 2] (FFCO[subscript 2]) emissions spatially at the building/street level and temporally at the hourly level. Hestia FFCO[subscript 2] emissions are provided in the form of a group of sector-specific vector layers with point, line, and polygon sources to support carbon cycle science and climate policy. Application to carbon cycle science, in particular, requires regular gridded data in order to link surface carbon fluxes to atmospheric transport models. However, the heterogeneity and complexity of FFCO[subscript 2] sources within regular grids is sensitive to spatial resolution. From the perspective of ...

Contributors
Liang, Jianming, Gurney, Kevin, O'Keeffe, Darragh, et al.
Created Date
2017-05-19