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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  11 Aug 2020

11 Aug 2020

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This preprint is currently under review for the journal ACP.

Anthropogenic and natural controls on atmospheric δ13C-CO2 variations in the Yangtze River Delta: Insights from a carbon isotope modeling framework

Cheng Hu1,2, Jiaping Xu3, Cheng Liu4, Yan Chen3, Dong Yang5, Wenjing Huang2, Lichen Deng6, Shoudong Liu2, Timothy J. Griffis7, and Xuhui Lee8 Cheng Hu et al.
  • 1College of Biology and the Environment, Joint Center for sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China
  • 2Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change (ILCEC), Nanjing University of Information, Science & Technology, Nanjing, 210044, China
  • 3Jiangsu Climate Center, China Meteorological Administration, Jiangsu Nanjing 210009, China
  • 4Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution, East China University of Technology, Nanchang 330013, China
  • 5Ningbo Meteorological Observatory, Ningbo 315012, China
  • 6Ecological Meteorology Center, Jiangxi Meteorological Bureau, Nanchang 330096, China
  • 7Department of Soil, Water, and Climate, University of Minnesota-Twin Cities, St. Paul, Minnesota, USA
  • 8School of Forestry and Environmental Studies, Yale University, New Haven, Connecticut, USA

Abstract. The atmospheric CO2 mixing ratio and its δ13C-CO2 composition contain important CO2 sink and source information spanning from ecosystem to global scales. The observation and simulation for both CO2 and its carbon isotope ratio (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 v432 CO2 inventories to simulate hourly CO2 mixing ratios and δ13C-CO2, evaluated these simulations with observations, and constrained the anthropogenic CO2 emission categories. Our study shows 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 performed well in reproducing the observed diel and seasonal atmospheric δ13C-CO2 variations; (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 variations. These findings support 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.

Cheng Hu et al.

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Cheng Hu et al.


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Latest update: 29 Sep 2020
Publications Copernicus
Short summary
70 % of global CO2 emissions were emitted from urban landscapes. The Yangtze River Delta (YRD) ranks as one of the most densely populated regions in the world and is an anthropogenic CO2 hotspot. Besides the anthropogenic factors, natural ecosystems and croplands act as significant CO2 sinks and sources. Independent quantification of the fossil and cement CO2 emission and assessment of their impact on atmospheric δ13C-CO2 have potential to improve our understanding of urban CO2 cycling.
70 % of global CO2 emissions were emitted from urban landscapes. The Yangtze River Delta (YRD)...