基于移动传感器的城市道路颗粒物污染特征

为实时分析城市道路环境中PM污染的变化特征，以出租车作为PM传感器的载体，对济南市道路环境进行了3个月的监测，并结合监测站的监测数据，对道路环境中PM的污染特征进行了分析.以核密度估计的方法提取了道路环境的PM“基线”，并量化了道路环境的排放贡献.结果表明，济南市PM污染严重的路段并不是位于交通较为密集的市区，而是集中在道路较为稀疏的郊区.将济南市路网系统划分为1021段道路，其中65%的路段PM_2.5浓度集中在43~46μg/m³，PM₁₀浓度在55~70μg/m³.相对于城市环境（监测站），早晚高峰尤其早高峰对于道路环境（传感器）的影响更为显著.通过提取的PM“基线”和传感器的小时均值，将传感器的测量信号分为背景浓度信号和排放浓度信号.研究期间，PM_2.5区域污染和排放占比分别为78.6%和21.4%，对于PM₁₀而言，区域污染和排放占比分别为71.9%和28.1%.

Pollution characteristics of particulate matter in urban roads: high spatial and temporal resolution monitoring based on mobile sensors

In order to analyze the change characteristics of particle pollution in urban road environment in real time, we took taxi as the carrier of PM sensor to monitor the road environment particles in Jinan for 3monthsand analyzed the pollution characteristics under the road environment, based on the monitoring data of mobile sensors and monitoring stations. Finally, we extracted thePM baseline of the road via the method of the kernel density estimation, and quantified the emissioncontributionsin the road environment. The heavily polluted areas of Jinan were not located in the densely populated city centre, but concentrated in the sparsely populated suburbs. The road network system in Jinan was divided into 1021 sections, of which 65% the PM_2.5 concentration was concentrated at 43~46μg/m³, and PM₁₀ concentration was concentrated at 55~70μg/m³. Compared with the urban environment (monitoring stations), the pollution of road environment (sensors) in Jinan was seriously affected by thepeaktime, especially the morning peak time. The sensor monitoring signal was divided into regional pollution signals and emission pollution signals based on the extracted PM baseline and the average value per hour of sensors. During the study, for PM_2.5, the regional pollution and emission ratio was 78.6% and 21.4%respectively and that was 71.9%, and 28.1% respectively for PM₁₀.