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Anthropogenic and natural controls on atmospheric delta C-13-CO2 variations in the Yangtze River delta: insights from a carbon isotope modeling framework

Xuhui Lee and 9 other contributors

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    Abstract

    The atmospheric carbon dioxide (CO2) mixing ratio and its carbon isotope (delta C-13-CO2) composition contain important CO2 sink and source information spanning from ecosystem to global scales. The observation and simulation for both CO2 and delta C-13-CO2 can be used to constrain regional emissions and better understand the anthropogenic and natural mechanisms that control delta C-13-CO2 variations. Such work remains rare for urban environments, especially megacities. Here, we used near-continuous CO2 and delta C-13-CO2 measurements, from September 2013 to August 2015, and inverse modeling to constrain the CO2 budget and investigate the main factors that dominated delta C-13-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 delta C-13-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 delta C-13-CO2 variations, and (3) anthropogenic CO2 emissions played a much larger role than ecosystems in controlling the delta C-13-CO2 seasonality. When excluding ecosystem respiration and photosynthetic discrimination in the YRD area, delta C-13-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 delta(s) (the mixture of delta C-13-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.