The Beijing–Tianjin–Hebei (BTH) region has encountered increasingly severe and frequent haze pollution during recent decades. This study reveals that El Niño–Southern Oscillation (ENSO) has distinctive impacts on interannual variations of haze pollution over BTH in early and late winters. The impact of ENSO on the haze pollution over the BTH is strong in early winter, but weak in late winter. In early winter, ENSO-related sea surface temperature anomalies generate double-cell Walker circulation anomalies, with upward motion anomalies over the tropical central-eastern Pacific and tropical Indian Ocean, and downward motion anomalies over the tropical western Pacific. The ascending motion and enhanced atmospheric heating anomalies over the tropical Indian Ocean trigger atmospheric teleconnection propagating from the north Indian Ocean to East Asia, and result in the generation of an anticyclonic anomaly over Northeast Asia. The associated southerly anomalies to the west side lead to more serious haze pollution via reducing surface wind speed and increasing low-level humidity and the thermal inversion. The strong contribution of the Indian Ocean heating anomalies to the formation of the anticyclonic anomaly over Northeast Asia in early winter can be confirmed by atmospheric model numerical experiments. In late winter, vertical motion and precipitation anomalies are weak over the tropical Indian Ocean related to ENSO. As such, ENSO cannot induce a clear anticyclonic anomaly over Northeast Asia via atmospheric teleconnection, and thus has a weak impact on the haze pollution over BTH. Further analysis shows that stronger ENSO-induced atmospheric heating anomalies over the tropical Indian Ocean in early winter are partially due to higher mean SST and precipitation there. Significance Statement: There exist large discrepancies regarding the contribution of El Niño–Southern Oscillation (ENSO) events to the wintertime haze pollution over North China. Several studies have indicated that ENSO has a weak impact on the haze pollution over North China. However, some studies have argued that ENSO events can exert impacts on the occurrence of haze pollution over North China. In this study, we present evidence to demonstrate that ENSO has distinctive impacts on interannual variations of the haze pollution over the Beijing–Tianjin–Hebei (BTH) region in North China in early and late winters. Specifically, ENSO has a strong impact on the haze pollution over BTH in early winter, whereas the impact of ENSO on the haze pollution over BTH is fairly weak in late winter. Results of this study could reconcile the discrepancy of previous studies about the impact of ENSO on the haze pollution over North China.

Haze is a majorly disastrous type of weather in China, especially central and eastern of China. The development of haze is mainly caused by highly concentrated fine particles (PM_2.5) on a regional scale. Here, we present the results from an autumn and winter study conducted from 2013 to 2020 in seven highly polluted areas (27 representative stations) in central and eastern China to analyze the growth mechanism of PM_2.5. At the same time, taking Beijing Station as an example, the characteristics of aerosol composition and particle size in the growth phase are analyzed. Taking into account the regional and inter-annual differences of fine particles (PM_2.5) distribution, the local average PM_2.5 growth value of the year is used as the boundary value for dividing slow, rapid, and explosive growth (only focuses on the hourly growth rate greater than 0). The average value of PM_2.5 in the autumn and winter of each regional representative station shows a decreasing trend as a whole, especially after 2017, whereby the decreasing trend was significant. The distribution value of +ΔPM_2.5 (PM_2.5 hourly growth rate) in the north of the Huai River is lower than that in the south of the Huai River, and both of the +ΔPM_2.5 after 2017 showed a significant decreasing trend. The average PM_2.5 threshold before the explosive growth is 70.8 µg m⁻³, and the threshold that is extremely prone to explosive growth is 156 µg m⁻³ to 277 µg m⁻³ in north of the Huai River. For the area south of the Huai River, the threshold for PM_2.5 explosive growth is relatively low, as a more stringent threshold also puts forward stricter requirements on atmospheric environmental governance. For example, in Beijing, the peak diameters gradually shift to larger sizes when the growth rate increases. The number concentration increasing mainly distributed in Aitken mode (AIM) and Accumulation mode (ACM) during explosive growth. Among the various components of submicron particulate matter (PM₁), organic aerosol (OA), especially primary OA (POA), have become one of the most critical components for the PM_2.5 explosive growth in Beijing. During the growth period, the contribution of secondary particulate matter (SPM) to the accumulated pollutants is significantly higher than that of primary particulate matter (PPM). However, the proportion of SPM gradually decreases when the growth rate increases. The contribution of the PPM can reach 48% in explosive growth. Compared to slow and rapid growth, explosive growth mainly occurs in the stable atmosphere of higher humidity, lower pressure, lower temperature, small winds, and low mixed layers.

In this study, based on the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data, the reliability and performances of their application on clean days and polluted days (based on the PM_2.5 mass concentrations) in Beijing were assessed. Conventional meteorological factors and diagnostic physical quantities from the NCEP/FNL data were compared with the L-band radar observations in Beijing in the autumns and winters of 2017–2019. The results indicate that the prediction reliability of the temperature was the best compared with those of the relative humidity and wind speed. It is worth noting that the relative humidity was lower and the near-surface wind speed was higher on polluted days from the NCEP/FNL data than from the observations. As far as diagnostic physical quantity is concerned, it was revealed that the temperature inversion intensity depicted by the NCEP/FNL data was significantly lower than that from the observations, especially on polluted days. For example, the difference in the temperature inversion intensity between the NCEP/FNL data and the observation ranged from −0.56 to −0.77 °C on polluted days. In addition, the difference in the wind shears between the NCEP/FNL reanalysis data and the observations increased to 0.40 m/s in the lower boundary layer on polluted days compared with that on clean days. Therefore, it is suggested that the underestimation of the relative humidity and temperature inversion intensity, and the overestimation of the near-surface wind speed should be seriously considered in simulating the air quality in the model, particularly on polluted days, which should be focused on more in future model developments.

Meteorological observation data from 843 national basic/base stations of the China were used to analyze the spatial and temporal distributions of haze in China. The area where there were more than 30 days of haze annually expanded gradually. The average number of haze days across China from 2001 to 2016 was 22.9d. The number of haze days increased gradually from 2001 to 2004 then declined slightly from 2004 to 2012. In 2013, the number of haze days increased to the highest level but then decreased through 2016. The annual number of haze episodes demonstrated a similar trend to the number of haze days. From 2014 to 2016, the cold air was weaker than in the past 30 years. At the same time, the number of breeze days increased and average wind speed decreased. The meteorological conditions were favorable for the formation of haze in China from 2014 to 2016. However, annual haze days, NO2 and SO2 from the OMI (Ozone Monitoring Instrument) data decreased in the three regions from 2014 to 2016, which implies that the emission control program conducted by the Chinese government was effective.