Air pollution monitoring for chemical industrial parks suffers from sensor deficiency. To address this problem, this work focuses on mobile monitoring station solutions to complement the fixed measurement deficiency. Flexibility in measurement location makes the mobile solution advantageous over fixed stations not only in providing sufficient number of measurements to satisfy the traceability condition, but also in the possibility to design monitoring route optimally according to real-time wind directions. By taking these advantages, this work proposes a new method for optimal mobile route design so that the inference of uncertainties on the accuracy of source rate estimation is minimized. Based on the linear relationship between the concentration measurements and source emission rates, the effect of measurement noises on the estimation error is derived as an amplification factor through numerical analysis, then, the optimal monitoring route can be determined by minimizing the amplification. Numerical and real case studies are presented to test the performance of the method. The results suggest that the approach proposed can effectively improve the performance of source rate estimation by optimally choosing the monitoring route.

化工园区空气污染监测存在传感器缺陷。为了解决这个问题，这项工作的重点是移动监测站解决方案，以弥补固定测量的不足。测量位置的灵活性使得移动解决方案优于固定站，不仅在提供足够数量的测量以满足可追溯性条件方面，而且在根据实时风向优化设计监测路线的可能性方面。利用这些优点，本文提出了一种优化移动路由设计的新方法，从而最大限度地减少了不确定性对源速率估计精度的影响。基于浓度测量值与源排放率之间的线性关系，通过数值分析推导出测量噪声对估计误差的影响作为放大因子，进而通过最小化放大确定最优监测路径。给出了数值和实际案例研究来测试该方法的性能。结果表明，所提出的方法可以通过优化选择监测路径来有效提高源速率估计的性能。