基于气象资料的林芝地区空气质量动态预报方法研究
Air Quality Dynamic Prediction Method Based on Nyingchi Meteorological Data
中文摘要：
空气污染状况不仅与污染源排放有关，也与气温、降水等气象要素存在密切联系。建立区域气象资料与空气质量的关系，对研究空气质量及其变化具有重要的研究意义。由于空气污染与气象条件之间并非线性关系，将前20d的气象观测资料和实际的大气污染物浓度作为输入参数，动态建立每天的多元线性回归方程，代入预报气象数据求取SO2、NO2、PM10的预测值和空气污染指数（API）值。初步试报表明，以20d为时间窗进行滑动预报，充分考虑了空气污染与气象条件之间的复杂动态关系，克服了传统静态空气质量预报方法的缺点，能更高精度地预报林芝地区的空气质量，具有一定的应用和推广价值。
中文关键词：
：空气质量动态预报，多元线性回归模型，污染物浓度
KeyWords：
air quality prediction, multiple linear regression model, pollutant concentration
Abstract：
Air pollution is not only associated with emissions of pollutant sources, but also has close links with meteorological factors such as temperature and precipitation. Establishment of the relationship between regional meteorological data and air quality is of great importance of the study of air quality and its changes. Because of the non-linear relationship between air pollution and meteorological conditions, the meteorological data and the actual concentration of air pollutants 20 days before as an input parameter dynamically created the daily multiple linear regression equation, then substituted the forecast meteorological data with the obtained equation to solve the predictive values and air pollution index (API) values of SO2, NO2, and PM10. The preliminary test prediction demonstrated that the sliding forecast method of 20 days as a time window could more accurately forecast the air quality of the Nyingchi and had certain application and promotion values. By using this method, meteorologists took adequately into account the complex and dynamic relationship between air pollution and meteorological conditions, thus overcoming the shortcomings of the traditional static air quality forecasting method.