The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM${}_{2.5}$ low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.

中文翻译：

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使用低成本传感器网络和数据同化的哥伦比亚阿布拉河谷地城市空气质量建模

近年来，低空气质量网络的使用一直在增加，以研究城市污染动态。在这里，我们展示了针对官方监控网络的AburráValley运营中低成本网络的评估。结果表明，PM${}_{2。5}$低成本测量与官方网络所观察到的非常接近。另外，低成本可以使整个山谷中的浓度得到更高的空间表现。我们使用数据同化功能将低成本观测值与化学迁移模型“长期臭氧模拟-欧洲操作烟雾”（LOTOS-EUROS）集成在一起。低成本网络的两种不同配置已被同化：使用整个低成本网络（255个传感器），以及仅使用相对于官方网络的相关系数大于0.8的传感器进行高质量选择（115个传感器） ）。还对官方站点进行了比较，以比较密度更高的低成本网络对模型性能的影响。两种模拟均采用低成本模型，其性能要优于模型，而无需吸收和吸收官方网络。通过将低成本网络相对于其他模拟同化，还可以提高针对污染事件发出警告的能力。最后，与使用完整的低成本网络相比，使用高质量配置进行的仿真具有更低的误差值，这表明必须考虑质量和位置而不仅仅是传感器的总数。我们的结果表明，随着低成本传感器的最新发展，可以通过低成本网络数据同化来提高模型性能。与使用完整的低成本网络相比，使用高质量配置进行的仿真具有更低的误差值，这表明必须考虑质量和位置，而不仅仅是传感器的总数。我们的结果表明，随着低成本传感器的最新发展，可以通过低成本网络数据同化来提高模型性能。与使用完整的低成本网络相比，使用高质量配置进行的仿真具有更低的误差值，这表明必须考虑质量和位置，而不仅仅是传感器的总数。我们的结果表明，随着低成本传感器的最新发展，可以通过低成本网络数据同化来提高模型性能。