Matching Items (7)
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Description
Energy consumption in buildings, accounting for 41% of 2010 primary energy consumption in the United States (US), is particularly vulnerable to climate change due to the direct relationship between space heating/cooling and temperature. Past studies have assessed the impact of climate change on long-term mean and/or peak energy demands. However,

Energy consumption in buildings, accounting for 41% of 2010 primary energy consumption in the United States (US), is particularly vulnerable to climate change due to the direct relationship between space heating/cooling and temperature. Past studies have assessed the impact of climate change on long-term mean and/or peak energy demands. However, these studies usually neglected spatial variations in the “balance point” temperature, population distribution effects, air-conditioner (AC) saturation, and the extremes at smaller spatiotemporal scales, making the implications of local-scale vulnerability incomplete. Here I develop empirical relationships between building energy consumption and temperature to explore the impact of climate change on long-term mean and extremes of energy demand, and test the sensitivity of these impacts to various factors. I find increases in summertime electricity demand exceeding 50% and decreases in wintertime non-electric energy demand of more than 40% in some states by the end of the century. The occurrence of the most extreme (appearing once-per-56-years) electricity demand increases more than 2600 fold, while the occurrence of the once per year extreme events increases more than 70 fold by the end of this century. If the changes in population and AC saturation are also accounted for, the impact of climate change on building energy demand will be exacerbated.

Using the individual building energy simulation approach, I also estimate the impact of climate change to different building types at over 900 US locations. Large increases in building energy consumption are found in the summer, especially during the daytime (e.g., >100% increase for warehouses, 5-6 pm). Large variation of impact is also found within climate zones, suggesting a potential bias when estimating climate-zone scale changes with a small number of representative locations.

As a result of climate change, the building energy expenditures increase in some states (as much as $3 billion/year) while in others, costs decline (as much as $1.4 billion/year). Integrated across the contiguous US, these variations result in a net savings of roughly $4.7 billion/year. However, this must be weighed against the cost (exceeding $19 billion) of adding electricity generation capacity in order to maintain the electricity grid’s reliability in summer.
ContributorsHuang, Jianhua (Author) / Gurney, Kevin Robert (Thesis advisor) / Miller, Clark Anson (Committee member) / Rey, Sergio J (Committee member) / Georgescu, Matei (Committee member) / Arizona State University (Publisher)
Created2016
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Description

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

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.

ContributorsFeng, Sha (Author) / Lauvaux, Thomas (Author) / Newman, Sally (Author) / Rao, Preeti (Author) / Ahmadov, Ravan (Author) / Deng, Aijun (Author) / Diaz-Isaac, Liza I. (Author) / Duren, Riley M. (Author) / Fischer, Marc L. (Author) / Gerbig, Christoph (Author) / Gurney, Kevin (Author) / Huang, Jianhua (Author) / Jeong, Seongeun (Author) / Li, Zhijin (Author) / Miller, Charles E. (Author) / O'Keeffe, Darragh (Author) / Patarasuk, Risa (Author) / Sander, Stanley P. (Author) / Song, Yang (Author) / Wong, Kam W. (Author) / Yung, Yuk L. (Author) / College of Liberal Arts and Sciences (Contributor)
Created2016-07-22
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Description

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 CO2 data collected by the dense tower network

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 CO2 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 the INFLUX inversion case with a global 1.1 km ODIAC fossil fuel CO2 emission dataset, we further improved the ODIAC emission field and examined its utility as a prior for the city scale inversion. We disaggregated the 1.1 km ODIAC non-point source emissions using geospatial datasets such as the global road network data and satellite-data driven surface imperviousness data to a 30 . 30 m resolution. We assessed the impact of the improved emission field on the inversion result, relative to priors in previous studies (Hestia and ODIAC). The posterior total emission estimate (5.1 MtC/yr) remains statistically similar to the previous estimate with ODIAC (5.3 MtC/yr). However, the distribution of the flux corrections was very close to those of Hestia inversion and the model-observation mismatches were significantly reduced both in forward and inverse runs, even without hourly temporal changes in emissions. EIs reported by cities often do not have estimates of spatial extents. Thus, emission disaggregation is a required step when verifying those reported emissions using atmospheric models. Our approach offers gridded emission estimates for global cities that could serves as a prior for inversion, even without locally reported EIs in a systematic way to support city-level Measuring, Reporting and Verification (MRV) practice implementation.

ContributorsOda, Tomohiro (Author) / Lauvaux, Thomas (Author) / Lu, Dengsheng (Author) / Rao, Preeti (Author) / Miles, Natasha L. (Author) / Richardson, Scott J. (Author) / Gurney, Kevin (Author) / College of Liberal Arts and Sciences (Contributor)
Created2017-06-14
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Description

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

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 (Cff) 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 Cff 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 Cff 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.

ContributorsNewman, Sally (Author) / Xu, Xiaomei (Author) / Gurney, Kevin (Author) / Hsu, Ying Kuang (Author) / Li, King Fai (Author) / Jiang, Xun (Author) / Keeling, Ralph (Author) / Feng, Sha (Author) / O'Keeffe, Darragh (Author) / Patarasuk, Risa (Author) / Wong, Kam Weng (Author) / Rao, Preeti (Author) / Fischer, Marc L. (Author) / Yung, Yuk L. (Author) / College of Liberal Arts and Sciences (Contributor)
Created2016-03-22
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Description

The INFLUX experiment has taken multiple approaches to estimate the carbon dioxide (CO2) flux in a domain centered on the city of Indianapolis, Indiana. One approach, Hestia, uses a bottom-up technique relying on a mixture of activity data, fuel statistics, direct flux measurement and modeling algorithms. A second uses a

The INFLUX experiment has taken multiple approaches to estimate the carbon dioxide (CO2) flux in a domain centered on the city of Indianapolis, Indiana. One approach, Hestia, uses a bottom-up technique relying on a mixture of activity data, fuel statistics, direct flux measurement and modeling algorithms. A second uses a Bayesian atmospheric inverse approach constrained by atmospheric CO2 measurements and the Hestia emissions estimate as a prior CO2 flux. The difference in the central estimate of the two approaches comes to 0.94 MtC (an 18.7% difference) over the eight-month period between September 1, 2012 and April 30, 2013, a statistically significant difference at the 2-sigma level. Here we explore possible explanations for this apparent discrepancy in an attempt to reconcile the flux estimates. We focus on two broad categories: 1) biases in the largest of bottom-up flux contributions and 2) missing CO2 sources. Though there is some evidence for small biases in the Hestia fossil fuel carbon dioxide (FFCO2) flux estimate as an explanation for the calculated difference, we find more support for missing CO2 fluxes, with biological respiration the largest of these. Incorporation of these differences bring the Hestia bottom-up and the INFLUX inversion flux estimates into statistical agreement and are additionally consistent with wintertime measurements of atmospheric 14CO2. We conclude that comparison of bottom-up and top-down approaches must consider all flux contributions and highlight the important contribution to urban carbon budgets of animal and biotic respiration. Incorporation of missing CO2 fluxes reconciles the bottom-up and inverse-based approach in the INFLUX domain.

ContributorsGurney, Kevin (Author) / Liang, Jianming (Author) / Patarasuk, Risa (Author) / O'Keeffe, Darragh (Author) / Huang, Jianhua (Author) / Hutchins, Maya (Author) / Lauvaux, Thomas (Author) / Turnbull, Jocelyn C. (Author) / Shepson, Paul B. (Author) / College of Liberal Arts and Sciences (Contributor)
Created2017-08-03
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Description

The ‘Hestia Project’ uses a bottom-up approach to quantify fossil fuel CO2(FFCO2) emissions spatially at the building/street level and temporally at the hourly level. Hestia FFCO2 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

The ‘Hestia Project’ uses a bottom-up approach to quantify fossil fuel CO2(FFCO2) emissions spatially at the building/street level and temporally at the hourly level. Hestia FFCO2 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 FFCO2 sources within regular grids is sensitive to spatial resolution. From the perspective of a data provider, we need to find a balance between resolution and data volume so that the gridded data product retains the maximum amount of information content while maintaining an efficient data volume.

The Shannon entropy determines the minimum bits that are needed to encode an information source and can serve as a metric for the effective information content. In this paper, we present an analysis of the Shannon entropy of gridded FFCO2 emissions with varying resolutions in four Hestia study areas, and find: (1) the Shannon entropy increases with smaller grid resolution until it reaches a maximum value (the max-entropy resolution); (2) total emissions (the sum of several sector-specific emission fields) show a finer max-entropy resolution than each of the sector-specific fields; (3) the residential emissions show a finer max-entropy resolution than the commercial emissions; (4) the max-entropy resolution of the onroad emissions grid is closely correlated to the density of the road network. These findings suggest that the Shannon entropy can detect the information effectiveness of the spatial resolution of gridded FFCO2 emissions. Hence, the resolution-entropy relationship can be used to assist in determining an appropriate spatial resolution for urban CO2 flux studies. We conclude that the optimal spatial resolution for providing Hestia total FFCO2 emissions products is centered around 100 m, at which the FFCO2 emissions data can not only fully meet the requirement of urban flux integration, but also be effectively used in understanding the relationships between FFCO2 emissions and various social-economic variables at the U.S. census block group level.

ContributorsLiang, Jianming (Author) / Gurney, Kevin (Author) / O'Keeffe, Darragh (Author) / Hutchins, Maya (Author) / Patarasuk, Risa (Author) / Huang, Jianhua (Author) / Song, Yang (Author) / Rao, Preeti (Author) / College of Liberal Arts and Sciences (Contributor)
Created2017-05-19
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Description

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

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.

ContributorsWong, Clare K. (Author) / Pongetti, Thomas J. (Author) / Oda, Tom (Author) / Rao, Preeti (Author) / Gurney, Kevin (Author) / Newman, Sally (Author) / Duren, Riley M. (Author) / Miller, Charles E. (Author) / Yung, Yuk L. (Author) / Sander, Stanley P. (Author) / College of Liberal Arts and Sciences (Contributor)
Created2016-10-26