Air pollution of chemical industrial parks (CIPs) is becoming increasingly severe, which has major impacts on the health of local residents. Therefore, source term estimation (STE) is of high importance to find the source locations and back-calculate the source emission rates based on the ambient concentration measurements and meteorological information. However, the number of the ambient sensors is far less than the one of pollution sources for CIPs. This issue of sensor deficiency makes the unknown source parameters untraceable. In this paper, the concept of traceability is introduced to propose a condition to explain when the STE problem has a unique solution. Then an approach using measurements at multiple time points for estimating the emission rate of each source is proposed. In order to satisfy the condition of traceability, the coefficient matrix can be expanded by augmenting measurement samples collected at different time instances with different wind directions when the emission rates keep unchanged. Furthermore, based on the rank of the coefficient matrix, the problem can be classified as fully traceable, partially traceable, and untraceable. Then, the regularized least squares method is applied to estimate the source rates in real-time. Some test results with a simulated scenario demonstrate that the source rate can be reliably estimated with the method proposed. Finally, the limitations and conclusions of the method are stated.

化学工业园区（CIP）的空气污染日益严重，对当地居民的健康造成重大影响。因此，源项估计（STE）对于找到源位置并根据环境浓度测量和气象信息反算源排放率非常重要。然而，环境传感器的数量远远少于CIP的污染源之一。传感器缺陷的这个问题使得未知的源参数无法追踪。在本文中，可追溯性的概念被引入以提出一个条件来解释 STE 问题何时具有唯一解。然后提出了一种使用多个时间点的测量值来估计每个源的排放率的方法。为满足可追溯性条件，在排放速率保持不变的情况下，可以通过增加在不同风向的不同时间实例收集的测量样本来扩展系数矩阵。此外，根据系数矩阵的秩，可以将问题分为完全可追溯、部分可追溯和不可追溯。然后，应用正则化最小二乘法实时估计源速率。一些模拟场景的测试结果表明，使用所提出的方法可以可靠地估计源速率。最后，说明了该方法的局限性和结论。问题可分为完全可追踪、部分可追踪和不可追踪。然后，应用正则化最小二乘法实时估计源速率。一些模拟场景的测试结果表明，使用所提出的方法可以可靠地估计源速率。最后，说明了该方法的局限性和结论。问题可分为完全可追踪、部分可追踪和不可追踪。然后，应用正则化最小二乘法实时估计源速率。一些模拟场景的测试结果表明，使用所提出的方法可以可靠地估计源速率。最后，说明了该方法的局限性和结论。