A new method for multi-point pollution source identification

Abstract

Rapid and accurate identification of the characteristics (source location, number, and intensity) of pollution sources is essential for emergency assessment of contamination events. Compared with single-point source identification, the reconstruction of multiple sources is more challenging. In this study, a two-step inversion method is proposed for multi-point pollution source reconstruction from limited measurements with the number of sources unknown. The applicability of the proposed method is validated with a set of synthetic experiments corresponding to one-, two-, and three-point pollution sources. The results show that the number and locations of pollution sources are retrieved exactly the same as prescribed, and the source intensities are estimated with negligible errors. The algorithm exhibits good performance in single- and multi-point pollution source identification, and its accuracy and efficiency of identification do not deteriorate with the increase in the number of sources. Some limitations of the algorithm, together with its capabilities, are also discussed in this paper.摘要对于污染源源项特征 (数量,位置及排放强度) 的快速且精确估计是污染事件应急响应的关键. 与单点源估计相比, 多点源的重建更具挑战性. 本文提出了一种新的针对于多点源污染事件的两步反演算法, 该算法通过结合大气化学模式与有限的浓度观测数据以实现对于未知数量的多点源的准确估计. 在其计算过程中, 无需任何未知量的先验信息, 且可以自动识别污染源的数量, 并确定每一个污染源的位置及强度. 本文通过使用若干组理想试验验证了算法的适用性, 试验结果表明, 该算法可准确估计单点源, 两点源和三点源的个数及位置, 强度的估计误差可基本忽略, 且该算法的估计精度和计算效率不会随着点源个数的增加而减弱.