The impact of synoptic patterns on summertime ozone pollution in the North China Plain

Surface ozone pollution is a challenging environmental issue in most parts of China. In particular, the North China Plain (NCP) region suffers from the severest ozone pollution throughout the country. In addition to the emission of precursors, ozone concentration is closely related to meteorological conditions resulting from regional atmospheric circulation. In this study, we investigate the relationship between synoptic patterns and summertime ozone pollution in the NCP using the objective principal component analysis in T-mode (T-PCA) classification method. Four dominant synoptic patterns are identified during the summers of 2014–2018. The heaviest ozone pollution is found to be associated with a high pressure anomaly over the Northwest Pacific and a distinct low pressure center in Northeast China. The southwesterly wind surrounding the low pressure center brings dry, warm air from inland South China, resulting in a high temperature, low humidity environment in the NCP, which favors the chemical formation of surface ozone. Locally, this type is associated with a moderate planetary boundary layer height (PBLH) of ~860 m and a stronger warm anomaly within the boundary layer than the upper level. We also notice a non-linear relationship between surface ozone concentration and the PBLH, i.e., ozone concentration first increases with PBLH till ~0.9 km, and then remains stable. This initial increase may relate to enhanced mixing with upper levels where ozone concentration is typically higher than that near the surface. However, when PBLH further increases, this downward mixing effect is balanced with the stronger upward turbulent mixing so that surface ozone shows little change. The synoptic patterns identified here, however, is unlikely responsible for the observed increasing trend in ozone concentration over the NCP region. Our study sheds light on the meteorological contribution to surface ozone pollution in North China and provides a reference for the pollution control and prediction. © 2020 Elsevier B.V.