基于移动监测的大气污染物浓度分布实时监测方法研究

Real-time Monitoring of Air Pollutant[HJ3.3mm]Concentration Distribution Based on Mobile Monitoring

为了获取更加精准的空气质量数据,提出一种基于移动监测的大气污染物浓度分布实时监测方法。将不同站点的历史监测数据设定为时空图形序列,获取各个移动监测站点观测值之间的空间相关性,采用频率分布法和阈值技术提取大气污染物浓度分布特征。利用改进的神经网络对大气污染物浓度分布特征分类处理,引入高斯扩散模型展开污染源强反算,最终实现大气污染物浓度分布实时监测。实验结果表明,所提方法可以实时精准监测大气污染物浓度分布情况,实际应用效果好。

In order to obtain more accurate air quality data,a real-time monitoring method of air pollutant concentration distribution based on mobile monitoring was proposed.The study sets the historical monitoring data of different stations as a spatiotemporal graphical sequence to obtain the spatial correlation between the observed values of each mobile monitoring station.It uses frequency distribution method and threshold technology to extract the distribution characteristics of atmospheric pollutant concentration.An improved neural network is used to classify and process the characteristics of atmospheric pollutant concentration distribution,and a Gaussian diffusion model is introduced to carry out the inverse calculation of pollution source intensity,ultimately achieving real-time monitoring of atmospheric pollutant concentration distribution.The experimental results show that the proposed method can accurately monitor the concentration distribution of atmospheric pollutants in real time,and has good practical application effects.