Abstract
Abstract. 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.
Highlights
Compared with the 1980s, fog-haze pollution events have increased significantly in the recent decade in the Beijing and North China region
Aerosol particles in the atmosphere can be activated into cloud condensation nuclei (CCN), which participate in the formation of clouds and fog, meaning that modern fog-haze has involved a great deal of polluted aerosol particles (e.g. PM2.5)
It is seen from the figure that, without considering the emission impact (Fig. 1c), the distribution centres of the PLAM index are h index forecasts of Beijing and Baoding (Hebei), Beijing, Tianjin and part of the Hubei, Henan and Sichuan provinces
Summary
Compared with the 1980s, fog-haze pollution events have increased significantly in the recent decade in the Beijing and North China region. Synthetic impact analysis of pollution-related atmospheric dynamics, thermodynamics, and chemical processes, as well as study of foghaze prediction, has drawn much attention. Long-term observations have pointed out that, in the last 30 years, foghaze phenomena in the central and eastern part of China have become more and more serious due to anthropogenic emissions. To reduce the impact of fog-haze, as a strong weather disaster, special attention needs to be paid to atmospheric aerosol pollution (Zhang et al, 2013) Three-dimensional numerical modelling has improved to different degrees in meteorological services with regard to global air quality predictions (Gong et al, 2003;, McKeen, 2007; Moran, 2009; Rigby et al, 2008; Zhang et al, 2009).
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