论文标题
使用低成本传感器的高分辨率空气质量预测
High-Resolution Air Quality Prediction Using Low-Cost Sensors
论文作者
论文摘要
在空气质量监控网络中使用低成本传感器仍然是从业者中的一个备受关注的话题：它们比公共当局建立的传统空气质量监测站（几百美元，而数十万美元）以较低的准确性和健壮性为代价。本文介绍了一项案例研究，该案例研究在空气质量预测引擎中使用低成本传感器测量。该发动机预测美国的PM2.5和PM10浓度在几十米的范围内以非常高的分辨率。 它以官方空气质量监测站提供的测量，由全国4000多个低成本传感器的网络以及交通估算提供的测量值。我们表明，使用低成本传感器的测量值可显着提高发动机的准确性。特别是，我们在低成本传感器的密度与预测的准确性之间得出了牢固的联系：在一个区域中，低成本传感器越低，预测就越准确。作为例证，在低成本传感器密度最高的区域中，低成本传感器的测量值分别在PM2.5和PM10预测的准确性方面提高了25％和15％。 另一个有力的结论是，在某些低成本传感器密度的某些区域中，仅与官方监测站的测量值相比，发动机的性能要好于使用低成本传感器的测量值时的性能更好：这表明由低速器传感器组成的空气质量监测网络可有效监测空气质量。这是一个非常重要的结果，因为这样的监视网络可以便宜得多。
The use of low-cost sensors in air quality monitoring networks is still a much-debated topic among practitioners: they are much cheaper than traditional air quality monitoring stations set up by public authorities (a few hundred dollars compared to a few dozens of thousand dollars) at the cost of a lower accuracy and robustness. This paper presents a case study of using low-cost sensors measurements in an air quality prediction engine. The engine predicts jointly PM2.5 and PM10 concentrations in the United States at a very high resolution in the range of a few dozens of meters. It is fed with the measurements provided by official air quality monitoring stations, the measurements provided by a network of more than 4000 low-cost sensors across the country, and traffic estimates. We show that the use of low-cost sensors' measurements improves the engine's accuracy very significantly. In particular, we derive a strong link between the density of low-cost sensors and the predictions' accuracy: the more low-cost sensors are in an area, the more accurate are the predictions. As an illustration, in areas with the highest density of low-cost sensors, the low-cost sensors' measurements bring a 25% and 15% improvement in PM2.5 and PM10 predictions' accuracy respectively. An other strong conclusion is that in some areas with a high density of low-cost sensors, the engine performs better when fed with low-cost sensors' measurements only than when fed with official monitoring stations' measurements only: this suggests that an air quality monitoring network composed of low-cost sensors is effective in monitoring air quality. This is a very important result, as such a monitoring network is much cheaper to set up.
