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Estimation of Pollutant Emissions from the Road Traffic at a City Scale, and Its Sensitivity as Regards the Calibration of the Static Traffic Assignment Models

机译:关于城市规模道路交通污染物排放的估算及其对静态交通分配模型校准的敏感性

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In this work, we study how uncertainties on input data of the coupling traffic of the assignment and pollutant emission models affect the resulting traffic and pollutant emissions. We analyse the sensitivity of the approach as regards the scenario definition (O/D matrix and vehicle fleet composition) and as regards the calibration process, which mostly consists in fitting the speed-flow curves. Variations on scenario definition induce changes of about 15% on pollutant emissions and traffic whereas variations on speed-flow curves affect them by about 5%. Complementary analyses show that variation of the travel demand significantly influences traffic, variation of the vehicle fleet composition significantly influences particulate matter (PM), CO 2 and NO x emissions, while variation of the shape of speed-flow curve mainly influences the traffic speeds.
机译:在这项工作中,我们研究分配和污染物排放模型耦合流量输入数据的不确定性如何影响由此产生的流量和污染物排放。我们针对场景定义(O / D矩阵和车队组成)以及标定过程(主要是拟合速度-流量曲线)对方法的敏感性进行了分析。情景定义的变化导致污染物排放和交通量变化约15%,而速度-流量曲线的变化影响它们约5%。补充分析表明,出行需求的变化显着影响交通,车队组成的变化显着影响颗粒物(PM),CO 2和NO x排放,而速度-流量曲线形状的变化主要影响交通速度。

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