Matching Items (5)

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Monthly trends of methane emissions in Los Angeles from 2011 to 2015 inferred by CLARS-FTS observations

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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

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 %). 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.

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Date Created
  • 2016-10-26

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Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO2 emissions

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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

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 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 CO[subscript 2] emission products to evaluate the impact of the spatial resolution of the CO[subscript 2] emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO[subscript 2] concentrations. We find that high spatial resolution in the fossil fuel CO[subscript 2] emissions is more important than in the atmospheric model to capture CO[subscript 2] concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO[subscript 2] fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO[subscript 2] 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 CO[subscript 2] concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO[subscript 2] emissions monitoring in the LA megacity requires FFCO[subscript 2] emissions modelling with  ∼  1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.

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  • 2016-07-22

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Toward consistency between trends in bottom-up CO2 emissions and top-down atmospheric measurements in the Los Angeles megacity

Description

Large urban emissions of greenhouse gases result in large atmospheric enhancements relative to background that are easily measured. Using CO[subscript 2] mole fractions and Δ[superscript 14]C and δ[superscript 13]C values

Large urban emissions of greenhouse gases result in large atmospheric enhancements relative to background that are easily measured. Using CO[subscript 2] mole fractions and Δ[superscript 14]C and δ[superscript 13]C values of CO[subscript 2] 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 CO[subscript 2] contributions from fossil fuel combustion (C[subscript 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[subscript 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 CO[subscript 2] from our observations are used to infer seasonality of natural gas and petroleum combustion. The trend of CO[subscript 2] 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 CO[subscript 2] 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[subscript ff] from parts of the basin sampled by winds at different times of year, we find that variations in observed fossil fuel CO[subscript 2] reflect seasonal variations in wind direction. The seasonality of the local CO[subscript 2] 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 CO[subscript 2] signals are consistent with sampling the bottom-up Hestia-LA fossil CO[subscript 2] emissions product for sub-city source regions in the LA megacity domain when wind directions are considered.

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Date Created
  • 2016-03-22

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Optimizing the Spatial Resolution for Urban CO2 Flux Studies Using the Shannon Entropy

Description

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]

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 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 FFCO[subscript 2] 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 FFCO[subscript 2] emissions. Hence, the resolution-entropy relationship can be used to assist in determining an appropriate spatial resolution for urban CO[subscript 2] flux studies. We conclude that the optimal spatial resolution for providing Hestia total FFCO[subscript 2] emissions products is centered around 100 m, at which the FFCO[subscript 2] emissions data can not only fully meet the requirement of urban flux integration, but also be effectively used in understanding the relationships between FFCO[subscript 2] emissions and various social-economic variables at the U.S. census block group level.

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Date Created
  • 2017-05-19

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On the impact of granularity of space-based urban CO2 emissions in urban atmospheric inversions: A case study for Indianapolis, IN

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

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 the INFLUX inversion case with a global 1 . 1 km ODIAC fossil fuel CO[subscript 2] 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.

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Date Created
  • 2017-06-14