Abstract. 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.
Supplementary material to "Anthropogenic and natural controls on atmospheric
<i>δ</i><sup>13</sup>C-CO<sub>2</sub> variations in the Yangtze River Delta: Insights from a carbon isotope modeling framework"
