In the 2015 winter month of December, northern China witnessed the most severe air pollution phenomena since the 2013 winter haze events occurred. This triggered the first-ever red alert in the air pollution control history of Beijing, with an instantaneous fine particulate matter (PM_2. 5) concentration over 1 mg m⁻³. Air quality observations reveal large temporal–spatial variations in PM_2. 5 concentrations over the Beijing–Tianjin–Hebei (Jing-Jin-Ji) area between 2014 and 2015. Compared to 2014, the PM_2. 5 concentrations over the area decreased significantly in all months except November and December of 2015, with an increase of 36 % in December. Analysis shows that the PM_2. 5 concentrations are significantly correlated with the local meteorological parameters in the Jing-Jin-Ji area such as the stable conditions, relative humidity (RH), and wind field. A comparison of two month simulations (December 2014 and 2015) with the same emission data was performed to explore and quantify the meteorological impacts on the PM_2. 5 over the Jing-Jin-Ji area. Observation and modeling results show that the worsening meteorological conditions are the main reasons behind this unusual increase of air pollutant concentrations and that the emission control measures taken during this period of time have contributed to mitigate the air pollution ( ∼ 9 %) in the region. This work provides a scientific insight into the emission control measures vs. the meteorology impacts for the period.

: By analyzing the data of urban air pollutant measurements from 2013 to 2015 in Nanjing, East China, we found that the correlation coefficients between major atmospheric compound pollutants PM_2.5 and O₃ were respectively 0.40 in hot season (June, July and August) and −0.16 in cold season (December, January and February) with both passing the confidence level of 99%. This provides evidence for the inverse relations of ambient PM_2.5 and O₃ between cold and hot seasons in an urban area of East China. To understand the interaction of PM_2.5 and O₃ in air compound pollution, the underlying mechanisms on the inversion relations between cold and hot seasons were investigated from the seasonal variations in atmospheric oxidation and radiative forcing of PM_2.5 based on three-year environmental and meteorological data. The analyses showed that the augmentation of atmospheric oxidation could strengthen the production of secondary particles with the contribution up to 26.76% to ambient PM_2.5 levels. High O₃ concentrations in a strong oxidative air condition during hot season promoted the formation of secondary particles, which could result in a positive correlation between PM_2.5 and O₃ in hot season. In cold season with weak atmospheric oxidation, the enhanced PM_2.5 levels suppressed surface solar radiation, which could weaken O₃ production for decreasing ambient O₃ level with the low diurnal peaks. Under the high PM_2.5 level exceeding 115 μg·m⁻³, the surface O₃ concentration dropped to 12.7 μg·m⁻³ at noon with a significant inhibitory effect, leading to a negative correlation between PM_2.5 and O₃ in cold season. This observational study revealed the interaction of PM_2.5 and O₃ in air compound pollution for understanding the seasonal change of atmospheric environment.

Using surface meteorological observation and high-resolution emission data, this paper discusses the application of the PLAM/h index (Parameter Linking Air-quality to Meteorological conditions/haze) in the prediction of large-scale low visibility and fog-haze events. Based on the two-dimensional probability density function diagnosis model for emissions, the study extends the diagnosis and prediction of the meteorological pollution index PLAM to the regional visibility fog-haze intensity. The results show that combining the influence of regular meteorological conditions and emission factors together in the PLAM/h parameterization scheme is very effective in improving the diagnostic identification ability of the fog-haze weather in North China. The determination coefficients for four seasons (spring, summer, autumn, and winter) between PLAM/h and visibility observation are 0.76, 0.80, 0.96, and 0.86, respectively, and all of their significance levels exceed 0.001, showing the ability of PLAM/h to predict the seasonal changes and differences of fog-haze weather in the North China region. The high-value correlation zones are located in Jing-Jin-Ji (Beijing, Tianjin, Hebei), Bohai Bay rim, and southern Hebei–northern Henan, indicating that the PLAM/h index is related to the distribution of frequent heavy fog-haze weather in North China and the distribution of emission high-value zone. Through comparative analysis of the heavy fog-haze events and large-scale clear-weather processes in winter and summer, it is found that PLAM/h index 24 h forecast is highly correlated with the visibility observation. Therefore, the PLAM/h index has good capability in identification, analysis, and forecasting.

Using surface meteorological observation and high resolution emission data, this paper discusses the application of PLAM/h Index (Parameter Linking Air-quality to Meteorological conditions/haze) in the prediction of large-scale low visibility and fog-haze events. Based on the two-dimensional probability density function diagnosis model for emissions, the study extends the diagnosis and prediction of the meteorological pollution index PLAM to the regional visibility fog-haze intensity. The results show that combining the influence of regular meteorological conditions and emission factors together in the PLAM/h parameterization scheme is very effective in improving the diagnostic identification ability of the fog-haze weather in North China. The correlation coefficients for four seasons (spring, summer, autumn and winter) between PLAM/h and visibility observation are 0.76, 0.80, 0.96 and 0.86 respectively and all their significance levels exceed 0.001, showing the ability of PLAM/h to predict the seasonal changes and differences of fog-haze weather in the North China region. The high-value correlation zones are respectively located in Jing-Jin-Ji (Beijing, Tianjin, Hebei), Bohai Bay rim and the southern Hebei-northern Henan, indicating that the PLAM/h index has relations with the distribution of frequent heavy fog-haze weather in North China and the distribution of emission high-value zone. Comparatively analyzing the heavy fog-haze events and large-scale fine weather processes in winter and summer, it is found that PLAM/h index 24 h forecast is highly correlated to the visibility observation. Therefore, PLAM/h index has better capability of doing identification, analysis and forecasting.