PLAM – a meteorological pollution index for air quality and its applications in fog-haze forecasts in North China
Item
Title (Dublin Core)
PLAM – a meteorological pollution index for air quality and its applications in fog-haze forecasts in North China
Description (Dublin Core)
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.
Creator (Dublin Core)
Yang, Y. Q.
Wang, J. Z.
Gong, S. L.
Zhang, X. Y.
Wang, H.
Wang, Y. Q.
Wang, J.
Li, D.
Guo, J. P.
Date (Dublin Core)
2018-09-08
Type (Dublin Core)
Text
Format (Dublin Core)
application/pdf
Identifier (Dublin Core)
10.5194/acp-16-1353-2016
https://acp.copernicus.org/articles/16/1353/2016/
Source (Dublin Core)
eISSN: 1680-7324
Language (Dublin Core)
eng
