突发型大气污染源位置识别反演问题的数值模拟

在突发型大气污染事件中,能否根据临时监测数据对污染源的位置进行快速识别,对于城市大气污染源的控制管理以及改善城市空气质量意义重大.为了构建突发型大气污染源位置识别的空间反演算法,本文通过分析大气应急污染监测的临时采样数据,结合污染物浓度扩散模型,随机生成污染源和计算污染物浓度的空间分布,对突发型大气污染源进行定位并与实际测量结果进行对比分析,采用蒙特卡洛模拟(Monte Carlo simulation)对相关参数进行讨论,最终构建能对突发型大气污染源进行快速估计定位的空间反演算法.研究结果表明,本文构建的空间反演算法输出的污染源坐标与实际情况相符.因此,该算法可用于突发型大气污染源位置的快速识别.

Numerical simulation on source identification of accidentally occurring air pollution

Sources identification for accidentally occurring air pollution based on temporary monitoring data is critical for pollution control and environmental management for better air quality. The objective of this paper is to develop a spatial estimation algorithm to identify the pollutant source for single point source air pollution problem. Air pollutants dispersion models were used to estimate the spatial distribution of the pollutants concentration. Based on the monitoring data for when an air pollution event occurs, a Monte Carlo simulation was used to estimate the locations of the pollutant sources. Case studies showed that the estimated locations of the pollutant sources matched well with the reality. This indicates that the spatial algorithm can be used for air pollution sources identification for when an air pollution event occurs.