Spatiotemporal variations in urban CO <sub>2</sub> flux with land-use types in Seoul

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Abstract

Background

Cities are a major source of atmospheric CO ₂; however, understanding the surface CO ₂ exchange processes that determine the net CO ₂ flux emitted from each city is challenging owing to the high heterogeneity of urban land use. Therefore, this study investigates the spatiotemporal variations of urban CO ₂ flux over the Seoul Capital Area, South Korea from 2017 to 2018, using CO ₂ flux measurements at nine sites with different urban land-use types (baseline, residential, old town residential, commercial, and vegetation areas).

Results

Annual CO ₂ flux significantly varied from 1.09 kg C m ^− 2 year ^− 1 at the baseline site to 16.28 kg C m ^− 2 year ^− 1 at the old town residential site in the Seoul Capital Area. Monthly CO ₂ flux variations were closely correlated with the vegetation activity (r = − 0.61) at all sites; however, its correlation with building energy usage differed for each land-use type (r = 0.72 at residential sites and r = 0.34 at commercial sites). Diurnal CO ₂ flux variations were mostly correlated with traffic volume at all sites (r = 0.8); however, its correlation with the floating population was the opposite at residential (r = − 0.44) and commercial (r = 0.80) sites. Additionally, the hourly CO ₂ flux was highly related to temperature. At the vegetation site, as the temperature exceeded 24 ℃, the sensitivity of CO ₂ absorption to temperature increased 7.44-fold than that at the previous temperature. Conversely, the CO ₂ flux of non-vegetation sites increased when the temperature was less than or exceeded the 18 ℃ baseline, being three-times more sensitive to cold temperatures than hot ones. On average, non-vegetation urban sites emitted 0.45 g C m ^− 2 h ^− 1 of CO ₂ throughout the year, regardless of the temperature.

Conclusions

Our results demonstrated that most urban areas acted as CO ₂ emission sources in all time zones; however, the CO ₂ flux characteristics varied extensively based on urban land-use types, even within cities. Therefore, multiple observations from various land-use types are essential for identifying the comprehensive CO ₂ cycle of each city to develop effective urban CO ₂ reduction policies.

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Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use change (ELUC), mainly deforestation, are based on land use and land use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2009–2018), EFF was 9.5±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.9±0.02 GtC yr−1 (2.3±0.01 ppm yr−1), SOCEAN 2.5±0.6 GtC yr−1, and SLAND 3.2±0.6 GtC yr−1, with a budget imbalance BIM of 0.4 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in EFF was about 2.1 % and fossil emissions increased to 10.0±0.5 GtC yr−1, reaching 10 GtC yr−1 for the first time in history, ELUC was 1.5±0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5±0.9 GtC yr−1 (42.5±3.3 GtCO2). Also for 2018, GATM was 5.1±0.2 GtC yr−1 (2.4±0.1 ppm yr−1), SOCEAN was 2.6±0.6 GtC yr−1, and SLAND was 3.5±0.7 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 407.38±0.1 ppm averaged over 2018. For 2019, preliminary data for the first 6–10 months indicate a reduced growth in EFF of +0.6 % (range of −0.2 % to 1.5 %) based on national emissions projections for China, the USA, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budget are consistently estimated over the period 1959–2018, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations shows (1) no consensus in the mean and trend in land use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018a, b, 2016, 2015a, b, 2014, 2013). The data generated by this work are available at https://doi.org/10.18160/gcp-2019 (Friedlingstein et al., 2019).

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Author and article information

Contributors

Sujong Jeong:

ORCID: http://orcid.org/0000-0003-4586-4534

sujong@snu.ac.kr

Journal

Journal ID (nlm-ta): Carbon Balance Manag

Journal ID (iso-abbrev): Carbon Balance Manag

Title: Carbon Balance and Management

Publisher: Springer International Publishing (Cham )

ISSN (Electronic): 1750-0680

Publication date (Electronic): 3 May 2022

Publication date PMC-release: 3 May 2022

Publication date Collection: December 2022

Volume: 17

Electronic Location Identifier: 3

Affiliations

[1 ]GRID grid.31501.36, ISNI 0000 0004 0470 5905, Department of Environmental Planning, Graduate School of Environmental Studies, , Seoul National University, ; Seoul, Republic of Korea

[2 ]GRID grid.263333.4, ISNI 0000 0001 0727 6358, Department of Climate and Environment, , Sejong University, ; Seoul, Republic of Korea

[3 ]GRID grid.482505.e, ISNI 0000 0004 0371 9491, National Institute of Meteorological Sciences, ; 63568 Jeju, Republic of Korea

Author information

Sujong Jeong http://orcid.org/0000-0003-4586-4534

Article

Publisher ID: 206

DOI: 10.1186/s13021-022-00206-w

PMC ID: 9066853

PubMed ID: 35503187

SO-VID: 677072c8-fb4a-4a09-9a92-405e9ed7497c

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 13 April 2021

Date accepted : 15 April 2022

Custom metadata

ScienceOpen disciplines: Environmental change

Keywords: co2 flux,annual cycle of co2 flux,diurnal cycle of co2 flux,urban,eddy covariance,co2 emissions,land-use types,seoul

Data availability:

ScienceOpen disciplines: Environmental change

Keywords: co2 flux, annual cycle of co2 flux, diurnal cycle of co2 flux, urban, eddy covariance, co2 emissions, land-use types, seoul