空气污染预报是根据气象条件(风、稳定度、降水及天气形势等)和污染源排放悄况对某个区域未来的污染浓度及空间分布发出预报。按内容一般可分为两类: —是空气污染气象预报(即潜势预报),主要预测未来的气象条件对大气中污染物的稀释扩散是否有利; 另一种是空气污染浓度预报, 主要根据气象参数和污染资料预测出污染物的浓度分布。
空气污染预报属于正问题,而从污染物浓度来求解扩散系数则属于反问题。
Air pollution prediction is a direct problem, and deriving diffusion coefficients from the concentration of pollutants is an inverse problem.
首次提出了空气质量环境背景值的确定等提高城市空气污染预报准确率的有效措施。
The effective measures that determined background value of urban air pollution and improved forecast accuracy was proposed.
在模型中既考虑了气象条件的作用,又考虑了污染排放量和起报日的污染浓度,与以往的空气污染预报统计模型相比,所依据的物理基础更可信一些。
In this model the effect of meteorological element, output and concentration of air pollutant were considered, so it's physical foundation may be more believable than pure statistics model.
应用推荐