TY - JOUR
T1 - Anthropogenic and natural controls on atmospheric δ13C-CO2 variations in the Yangtze River delta
T2 - Insights from a carbon isotope modeling framework
AU - Hu, Cheng
AU - Xu, Jiaping
AU - Liu, Cheng
AU - Chen, Yan
AU - Yang, Dong
AU - Huang, Wenjing
AU - Deng, Lichen
AU - Liu, Shoudong
AU - Griffis, Timothy J.
AU - Lee, Xuhui
N1 - Publisher Copyright:
© 2021 Cheng Hu et al.
PY - 2021/7/6
Y1 - 2021/7/6
N2 - The atmospheric carbon dioxide (CO2) mixing ratio and its carbon isotope (δ13C-CO2) composition contain important CO2 sink and source information spanning from ecosystem to global scales. The observation and simulation for both CO2 and δ13C-CO2 can be used to constrain regional emissions and better understand the anthropogenic and natural mechanisms that control δ13C-CO2 variations. Such work remains rare for urban environments, especially megacities. Here, we used near-continuous CO2 and δ13C-CO2 measurements, from September 2013 to August 2015, and inverse modeling to constrain the CO2 budget and investigate the main factors that dominated δ13C-CO2 variations for the Yangtze River delta (YRD) region, one of the largest anthropogenic CO2 hotspots and densely populated regions in China. We used the WRF-STILT model framework with category-specified EDGAR v4.3.2 CO2 inventories to simulate hourly CO2 mixing ratios and δ13C-CO2, evaluated these simulations with observations, and constrained the total anthropogenic CO2 emission. We show that (1) top-down and bottom-up estimates of anthropogenic CO2 emissions agreed well (bias <6%) on an annual basis, (2) the WRF-STILT model can generally reproduce the observed diel and seasonal atmospheric δ13C-CO2 variations, and (3) anthropogenic CO2 emissions played a much larger role than ecosystems in controlling the δ13C-CO2 seasonality. When excluding ecosystem respiration and photosynthetic discrimination in the YRD area, δ13C-CO2 seasonality increased from 1.53‰ to 1.66‰. (4) Atmospheric transport processes in summer amplified the cement CO2 enhancement proportions in the YRD area, which dominated monthly δs (the mixture of δ13C-CO2 from all regional end-members) variations. These findings show that the combination of long-term atmospheric carbon isotope observations and inverse modeling can provide a powerful constraint on the carbon cycle of these complex megacities.
AB - The atmospheric carbon dioxide (CO2) mixing ratio and its carbon isotope (δ13C-CO2) composition contain important CO2 sink and source information spanning from ecosystem to global scales. The observation and simulation for both CO2 and δ13C-CO2 can be used to constrain regional emissions and better understand the anthropogenic and natural mechanisms that control δ13C-CO2 variations. Such work remains rare for urban environments, especially megacities. Here, we used near-continuous CO2 and δ13C-CO2 measurements, from September 2013 to August 2015, and inverse modeling to constrain the CO2 budget and investigate the main factors that dominated δ13C-CO2 variations for the Yangtze River delta (YRD) region, one of the largest anthropogenic CO2 hotspots and densely populated regions in China. We used the WRF-STILT model framework with category-specified EDGAR v4.3.2 CO2 inventories to simulate hourly CO2 mixing ratios and δ13C-CO2, evaluated these simulations with observations, and constrained the total anthropogenic CO2 emission. We show that (1) top-down and bottom-up estimates of anthropogenic CO2 emissions agreed well (bias <6%) on an annual basis, (2) the WRF-STILT model can generally reproduce the observed diel and seasonal atmospheric δ13C-CO2 variations, and (3) anthropogenic CO2 emissions played a much larger role than ecosystems in controlling the δ13C-CO2 seasonality. When excluding ecosystem respiration and photosynthetic discrimination in the YRD area, δ13C-CO2 seasonality increased from 1.53‰ to 1.66‰. (4) Atmospheric transport processes in summer amplified the cement CO2 enhancement proportions in the YRD area, which dominated monthly δs (the mixture of δ13C-CO2 from all regional end-members) variations. These findings show that the combination of long-term atmospheric carbon isotope observations and inverse modeling can provide a powerful constraint on the carbon cycle of these complex megacities.
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U2 - 10.5194/acp-21-10015-2021
DO - 10.5194/acp-21-10015-2021
M3 - Article
AN - SCOPUS:85109288590
SN - 1680-7316
VL - 21
SP - 10015
EP - 10037
JO - Atmospheric Chemistry and Physics
JF - Atmospheric Chemistry and Physics
IS - 13
ER -