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The distribution and influential factors of PM_(2.5) and CO_2 in urban rail carriages

机译:城市轨道车辆PM_(2.5)和CO_2的分布及其影响因素

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The promotion of 'Green Transport' has increased the importance of urban rail transit in China. Increased passenger flow and longer travel time have led to increased attention to in-carriage air quality in trains. In this study, CO2 and PM2.5 monitoring were conducted in subway train carriages in a city in northern China. The study accounts for a variety of factors both inside and outside of the train carriages, such as passenger volume and exterior environment. The results reveal that good air quality outside of the train, an above ground location and the use of platform screen doors could aid in the attainment of acceptable PM2.5 concentrations. In addition, linear models of CO2 and PM2.5 concentrations were established based on passenger density. The nonlinear recursive models were constructed using time-series analysis to reflect the cumulative effects of the amounts of CO2 and PM2.5. The spatial and temporal distributions show that, given a constant passenger density, the PM2.5 concentration is higher near the door area than in the seating area. CO2 concentrations varied in three stages, consistent with the change of local passenger load. Finally, a real-time optimized control method for fresh air volume and some suggestions are proposed to improve the in-carriage air quality of subway trains.
机译:促进“绿色运输”已经增加了中国城市轨道交通的重要性。旅客流量的增加和旅行时间的延长,引起了人们对火车车内空气质量的更多关注。在这项研究中,在中国北方城市的地铁车厢中进行了CO2和PM2.5监测。该研究考虑了火车车厢内部和外部的多种因素,例如乘客量和外部环境。结果表明,火车外的良好空气质量,高于地面的位置以及使用屏蔽门可以帮助达到可接受的PM2.5浓度。此外,根据乘客密度建立了CO2和PM2.5浓度的线性模型。使用时间序列分析构建非线性递归模型,以反映CO2和PM2.5量的累积影响。空间和时间分布表明,在恒定的乘客密度下,门区域附近的PM2.5浓度高于座位区域。 CO2浓度分为三个阶段变化,与当地乘客负荷的变化一致。最后,提出了一种新风量实时优化控制方法,并提出了改善地铁列车车厢内空气质量的一些建议。

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