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中文摘要: 通过分析北京城区4种主要空气污染物（SO2、NOX、CO、TSP）浓度的月、季变化特征，建立起均生函数预测模型。拟合及预报试验表明，这些预测模型不但可以很好地拟合空气污染浓度的变化趋势，而且还能够对未来几个月的空气污染浓度做出较准确的预测。
中文关键词: 空气污染，污染物浓度，预测
Abstract:A model of mean generating function prediction has been set up by analyzing characteristics of the monthly and seasonally change in the densities of four main pollution agents (SO2, NOX, CO,TSP)in Beijing city. The model fitting and forecast show that the model not only can fit the changing tendency of air pollution, but also can forecast air pollution density quite accurately.
keywords: air pollution,pollution density,forecast
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引用文本：
魏生生,林学范,1999.北京城区空气污染浓度长期预测[J].气象,25(1):43-47.
,1999.The Long-term Forecast of the Air Pollution Density in Beijing City[J].Meteor Mon,25(1):43-47.
魏生生,林学范,1999.北京城区空气污染浓度长期预测[J].气象,25(1):43-47.
,1999.The Long-term Forecast of the Air Pollution Density in Beijing City[J].Meteor Mon,25(1):43-47.