Lower tropospheric ozone over the North China Plain: variability and trends revealed by IASI satellite observations for 2008–2016
2018
Abstract. China is a highly polluted region, particularly the North China Plain (NCP).
However, emission reductions have been occurring in China for about the last
10 years; these reduction measures have been in effect since 2006 for SO 2 emissions and
since 2010 for NO x emissions. Recent studies have shown a
decrease in the NO 2 tropospheric column since 2013 that has been attributed to
the reduction in NO x emissions. Quantifying how these emission
reductions translate regarding ozone concentrations remains unclear due to
apparent inconsistencies between surface and satellite observations. In this
study, we use the lower tropospheric (LT) columns (surface – 6 km a.s.l. – above sea level)
derived from the IASI-A satellite instrument to describe the variability and
trend in LT ozone over the NCP for the 2008–2016 period. First, we investigate the IASI
retrieval stability and robustness based on the influence of atmospheric
conditions (thermal conditions and aerosol loading) and retrieval sensitivity
changes. We compare IASI-A observations with the independent IASI-B
instrument aboard the Metop-B satellite as well as comparing them with surface and ozonesonde
measurements. The conclusion from this evaluation is that the LT ozone columns
retrieved from IASI-A are reliable for deriving a trend representative of the
lower/free troposphere (3–5 km). Deseasonalized monthly time series of LT
ozone show two distinct periods: the first period (2008–2012) with no
significant trend ( −0.1 % yr −1 ) and a second period (2013–2016) with a
highly significant negative trend of −1.2 % yr −1 , which leads to an
overall significant trend of −0.77 % yr −1 for the 2008–2016 period. We
explore the dynamical and chemical factors that could explain these negative
trends using a multivariate linear regression model and chemistry transport
model simulations to evaluate the sensitivity of ozone to the reduction in
NO x emissions. The results show that the negative
trend observed from IASI for the 2013–2016 period is almost equally attributed to
large-scale dynamical processes and emissions reduction, with the large El Nino
event in 2015–2016 and the reduction of NO x emissions being
the main contributors. For the entire 2008–2016 period, large-scale
dynamical processes explain more than half of the observed trend, with a
possible reduction of the stratosphere–troposphere exchanges being the
main contributor. Large-scale transport and advection, evaluated using CO as
a proxy, only contributes to a small part of the trends ( ∼10 %). However,
a residual significant negative trend remains; this shows the limitation of
linear regression models regarding their ability to account for nonlinear processes such as ozone
chemistry and stresses the need for a detailed evaluation of changes in chemical
regimes with the altitude.
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