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 SO2 emissions and since 2010 for NOx emissions. Recent studies have shown a decrease in the NO2 tropospheric column since 2013 that has been attributed to the reduction in NOx 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 – 6kma.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 (3–5km). 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 NOx 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 Ni?o event in 2015–2016 and the reduction of NOx 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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