A Comparative Analysis of Anthropogenic CO2 Emissions at City Level Using OCO-2 Observations: A Global Perspective

Peng Fu; Yanhua Xie; Caitlin E. Moore; Soe Myint; Carl J. Bernacchi

doi:10.1029/2019EF001282

A Comparative Analysis of Anthropogenic CO₂ Emissions at City Level Using OCO-2 Observations: A Global Perspective

Peng Fu, Yanhua Xie, Caitlin E. Moore, Soe Myint, Carl J. Bernacchi

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

Abstract

Satellite observations of anthropogenic carbon dioxide (CO₂) emissions within urban settings offer unique potential to understand carbon sources and sinks and evaluate carbon mitigation strategies. Despite availability of column-averaged dry air mole fraction of CO₂ ((Formula presented.)) from Orbiting Carbon Observatory-2 (OCO-2), temporal variations of (Formula presented.) and their drivers in cities remain poorly understood due to inconsistent definitions of urban extent, diverse urban forms, and unresolved impacts of urban vegetation on carbon fluxes. To this end, this study revealed that OCO-2 (Formula presented.) measurements from 2014 to 2018 exhibited statistically significant seasonal and trend components for each city. A correlation analysis suggested a weak association between (Formula presented.) trends and fossil fuel CO₂ emissions ((Formula presented.)) trends but a close relationship between yearly average (Formula presented.) and (Formula presented.) trends. Vegetation abundance exhibited a negative relationship with the (Formula presented.) seasonality, though it only explained 21% of the variance. No statistically significant relationship between urban morphological factors (areal extent, complexity, and compactness) and temporal (Formula presented.) components was observed. However, urban morphological factors had a close relationship with the total amount of (Formula presented.) aggregated over the study period. Thus, it was speculated that urban morphological factors exerted their influence on (Formula presented.) through fossil fuel consumption. When only cities of high normalized difference vegetation index seasonality were used, statistically significant correlation coefficients between urban morphological factors and winter/summer averaged (Formula presented.) measurements were found. The variations of these correlation coefficients between leaf-on and leaf-off seasons stress the important role that urban trees play in mitigating carbon emissions in cities.

Original language	English (US)
Pages (from-to)	1058-1070
Number of pages	13
Journal	Earth's Future
Volume	7
Issue number	9
DOIs	https://doi.org/10.1029/2019EF001282
State	Published - Sep 1 2019

Keywords

OCO-2
carbon dioxide emissions
seasonal and trend modeling
urban form
urban vegetation

ASJC Scopus subject areas

General Environmental Science
Earth and Planetary Sciences (miscellaneous)

Access to Document

10.1029/2019EF001282

Cite this

@article{4bda9a7e52bc4330b77e7f2b92ddfd05,

title = "A Comparative Analysis of Anthropogenic CO2 Emissions at City Level Using OCO-2 Observations: A Global Perspective",

abstract = "Satellite observations of anthropogenic carbon dioxide (CO2) emissions within urban settings offer unique potential to understand carbon sources and sinks and evaluate carbon mitigation strategies. Despite availability of column-averaged dry air mole fraction of CO2 ((Formula presented.)) from Orbiting Carbon Observatory-2 (OCO-2), temporal variations of (Formula presented.) and their drivers in cities remain poorly understood due to inconsistent definitions of urban extent, diverse urban forms, and unresolved impacts of urban vegetation on carbon fluxes. To this end, this study revealed that OCO-2 (Formula presented.) measurements from 2014 to 2018 exhibited statistically significant seasonal and trend components for each city. A correlation analysis suggested a weak association between (Formula presented.) trends and fossil fuel CO2 emissions ((Formula presented.)) trends but a close relationship between yearly average (Formula presented.) and (Formula presented.) trends. Vegetation abundance exhibited a negative relationship with the (Formula presented.) seasonality, though it only explained 21% of the variance. No statistically significant relationship between urban morphological factors (areal extent, complexity, and compactness) and temporal (Formula presented.) components was observed. However, urban morphological factors had a close relationship with the total amount of (Formula presented.) aggregated over the study period. Thus, it was speculated that urban morphological factors exerted their influence on (Formula presented.) through fossil fuel consumption. When only cities of high normalized difference vegetation index seasonality were used, statistically significant correlation coefficients between urban morphological factors and winter/summer averaged (Formula presented.) measurements were found. The variations of these correlation coefficients between leaf-on and leaf-off seasons stress the important role that urban trees play in mitigating carbon emissions in cities.",

keywords = "OCO-2, carbon dioxide emissions, seasonal and trend modeling, urban form, urban vegetation",

author = "Peng Fu and Yanhua Xie and Moore, {Caitlin E.} and Soe Myint and Bernacchi, {Carl J.}",

note = "Funding Information: The XCO2 measurements used in this study were produced by the OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the OCO-2 data archive maintained at the NASA Goddard Earth Science Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets?project=OCO). The authors would also like to thank the ODIAC team for providing the fossil fuel consumption data at a global scale (http://db.cger.nies.go.jp/dataset/ODIAC/) and the NASA EOSDIS team for providing the monthly global 1-km NDVI data (https://lpdaac.usgs.gov/products/myd13a3v006/). The manuscript is entirely based on these publicly available data sets. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the U.S. Department of Agriculture. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer. Publisher Copyright: {\textcopyright} 2019. The Authors.",

year = "2019",

month = sep,

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doi = "10.1029/2019EF001282",

language = "English (US)",

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T1 - A Comparative Analysis of Anthropogenic CO2 Emissions at City Level Using OCO-2 Observations

T2 - A Global Perspective

AU - Fu, Peng

AU - Xie, Yanhua

AU - Moore, Caitlin E.

AU - Myint, Soe

AU - Bernacchi, Carl J.

N1 - Funding Information: The XCO2 measurements used in this study were produced by the OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the OCO-2 data archive maintained at the NASA Goddard Earth Science Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets?project=OCO). The authors would also like to thank the ODIAC team for providing the fossil fuel consumption data at a global scale (http://db.cger.nies.go.jp/dataset/ODIAC/) and the NASA EOSDIS team for providing the monthly global 1-km NDVI data (https://lpdaac.usgs.gov/products/myd13a3v006/). The manuscript is entirely based on these publicly available data sets. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the U.S. Department of Agriculture. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer. Publisher Copyright: © 2019. The Authors.

PY - 2019/9/1

Y1 - 2019/9/1

N2 - Satellite observations of anthropogenic carbon dioxide (CO2) emissions within urban settings offer unique potential to understand carbon sources and sinks and evaluate carbon mitigation strategies. Despite availability of column-averaged dry air mole fraction of CO2 ((Formula presented.)) from Orbiting Carbon Observatory-2 (OCO-2), temporal variations of (Formula presented.) and their drivers in cities remain poorly understood due to inconsistent definitions of urban extent, diverse urban forms, and unresolved impacts of urban vegetation on carbon fluxes. To this end, this study revealed that OCO-2 (Formula presented.) measurements from 2014 to 2018 exhibited statistically significant seasonal and trend components for each city. A correlation analysis suggested a weak association between (Formula presented.) trends and fossil fuel CO2 emissions ((Formula presented.)) trends but a close relationship between yearly average (Formula presented.) and (Formula presented.) trends. Vegetation abundance exhibited a negative relationship with the (Formula presented.) seasonality, though it only explained 21% of the variance. No statistically significant relationship between urban morphological factors (areal extent, complexity, and compactness) and temporal (Formula presented.) components was observed. However, urban morphological factors had a close relationship with the total amount of (Formula presented.) aggregated over the study period. Thus, it was speculated that urban morphological factors exerted their influence on (Formula presented.) through fossil fuel consumption. When only cities of high normalized difference vegetation index seasonality were used, statistically significant correlation coefficients between urban morphological factors and winter/summer averaged (Formula presented.) measurements were found. The variations of these correlation coefficients between leaf-on and leaf-off seasons stress the important role that urban trees play in mitigating carbon emissions in cities.

AB - Satellite observations of anthropogenic carbon dioxide (CO2) emissions within urban settings offer unique potential to understand carbon sources and sinks and evaluate carbon mitigation strategies. Despite availability of column-averaged dry air mole fraction of CO2 ((Formula presented.)) from Orbiting Carbon Observatory-2 (OCO-2), temporal variations of (Formula presented.) and their drivers in cities remain poorly understood due to inconsistent definitions of urban extent, diverse urban forms, and unresolved impacts of urban vegetation on carbon fluxes. To this end, this study revealed that OCO-2 (Formula presented.) measurements from 2014 to 2018 exhibited statistically significant seasonal and trend components for each city. A correlation analysis suggested a weak association between (Formula presented.) trends and fossil fuel CO2 emissions ((Formula presented.)) trends but a close relationship between yearly average (Formula presented.) and (Formula presented.) trends. Vegetation abundance exhibited a negative relationship with the (Formula presented.) seasonality, though it only explained 21% of the variance. No statistically significant relationship between urban morphological factors (areal extent, complexity, and compactness) and temporal (Formula presented.) components was observed. However, urban morphological factors had a close relationship with the total amount of (Formula presented.) aggregated over the study period. Thus, it was speculated that urban morphological factors exerted their influence on (Formula presented.) through fossil fuel consumption. When only cities of high normalized difference vegetation index seasonality were used, statistically significant correlation coefficients between urban morphological factors and winter/summer averaged (Formula presented.) measurements were found. The variations of these correlation coefficients between leaf-on and leaf-off seasons stress the important role that urban trees play in mitigating carbon emissions in cities.

KW - OCO-2

KW - carbon dioxide emissions

KW - seasonal and trend modeling

KW - urban form

KW - urban vegetation

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