Evaluating China's anthropogenic CO2 emissions inventories: a northern China case study using continuous surface observations from 2005 to 2009
Authors: Dayalu Archana , Munger J. William , Wang Yuxuan , Wofsy Steven C. , Zhao Yu , Nehrkorn Thomas , Nielsen Chris , McElroy Michael B. , Chang Rachel 
Published: March 2020

Abstract. China has pledged reduction of carbon dioxide (CO2)
emissions per unit of gross domestic product (GDP) by 60 %–65 % relative to 2005 levels,
and to peak carbon emissions overall by 2030. However, the lack of
observational data and disagreement among the many available
inventories makes it difficult for China to track progress toward
these goals and evaluate the efficacy of control measures. To
demonstrate the value of atmospheric observations for constraining
CO2 inventories we track the ability of CO2
concentrations predicted from three different CO2
inventories to match a unique multi-year continuous record of
atmospheric CO2. Our analysis time window includes the key
commitment period for the Paris Agreement (2005) and the Beijing
Olympics (2008). One inventory is China-specific and two are spatial
subsets of global inventories. The inventories differ in spatial
resolution, basis in national or subnational statistics, and reliance
on global or China-specific emission factors. We use a unique set of
historical atmospheric observations from 2005 to 2009 to evaluate the
three CO2 emissions inventories within China's heavily
industrialized and populated northern region accounting for
∼33 %–41 % of national emissions. Each anthropogenic
inventory is combined with estimates of biogenic CO2 within
a high-resolution atmospheric transport framework to model the time
series of CO2 observations. To convert the model–observation
mismatch from mixing ratio to mass emission rates we distribute it
over a region encompassing 90 % of the total surface influence in
seasonal (annual) averaged back-trajectory footprints (L_0.90
region). The L_0.90 region roughly corresponds to northern
China. Except for the peak growing season, where assessment of
anthropogenic emissions is entangled with the strong vegetation
signal, we find the China-specific inventory based on subnational data
and domestic field studies agrees significantly better with
observations than the global inventories at all timescales. Averaged
over the study time period, the unscaled China-specific inventory
reports substantially larger annual emissions for northern China
(30 %) and China as a whole (20 %) than the two unscaled
global inventories. Our results, exploiting a robust time series of
continuous observations, lend support to the rates and geographic
distribution in the China-specific inventory Though even long-term
observations at a single site reveal differences among inventories,
exploring inventory discrepancy over all of China requires a denser
observational network in future efforts to measure and verify
CO2 emissions for China both regionally and nationally. We
find that carbon intensity in the northern China region has decreased
by 47 % from 2005 to 2009, from approximately
4 kg of CO2 per USD (note that all references to USD in this paper refer to USD adjusted for purchasing power parity, PPP) in 2005 to about
2 kg of CO2 per USD in 2009
(Fig. 9c). However, the corresponding 18 % increase in
absolute emissions over the same time period affirms a critical point
that carbon intensity targets in emerging economies can be at odds
with making real climate progress. Our results provide an important
quantification of model–observation mismatch, supporting the increased
use and development of China-specific inventories in tracking China's
progress as a whole towards reducing emissions. We emphasize that this
work presents a methodology for extending the analysis to other
inventories and is intended to be a comparison of a subset of
anthropogenic CO2 emissions rates from inventories that were
readily available at the time this research began. For this study's
analysis time period, there was not enough spatially distinct
observational data to conduct an optimization of the inventories. The
primary intent of the comparisons presented here is not to judge
specific inventories, but to demonstrate that even a single site with
a long record of high-time-resolution observations can identify major
differences among inventories that manifest as biases in the
model–data comparison. This study provides a baseline analysis for
evaluating emissions from a small but important region within China,
as well a guide for determining optimal locations for future
ground-based measurement sites.