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Emission modelling of hazardous air pollutants from road transport at urban scale

机译:城市道路运输中有害空气污染物的排放模型

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This study is focused on the development of a modelling approach to quantify emissions of traffic-related hazardous air pollutants in urban areas considering complex road network and detailed data on transport activity. In this work a new version of the Transport Emission Model for line sources has been developed for hazardous pollutants (TREM-HAP). Emission factors for benzene, 1,3-butadiene, formaldehyde, acetaldehyde, acrolein, naphthalene and also particulate matter (PM2.5) were implemented and the model was extended to integrate a probabilistic approach for the uncertainty quantification using Monte-Carlo technique. The methodology has been applied to estimate road traffic emissions in Porto Urban Area, Portugal. Hourly traffic counts provided by an automatic counting system were used to characterise the spatial and temporal variability of the number of vehicles, vehicle categories and average speed at different road segments. The data for two summer and two winter months were processed to obtain probability density functions of the input parameters required for the uncertainty analysis. For quantification of cold start excess emissions, Origin-Destination matrix for daily trips was used as additional input information. Daily emissions of hazardous air pollutants from road traffic were analysed for the study area. The uncertainty of the emission estimates related to the transport activity factors range from as small as ?2 to +1.7% for acrolein and acetaldehyde on highways, to as large as ?33 to +70% for 1,3-butadiene considering urban street driving. An important contribution of cold start emissions to the total daily values was estimated thus achieving 45% in case of benzene. The uncertainty in transport activity data on resulting urban emission inventory highlights the most important parameter and reveals different sensitivity of the emission quantification to the input data. The methodology presented in this work allows the development of emission inventories for hazardous air pollutants with high spatial and temporal resolution in complex urban areas required for air quality modelling and exposure studies and could be used as a decision support tool.
机译:这项研究的重点是考虑到复杂的道路网络和有关运输活动的详细数据,开发一种建模方法来量化城市地区与交通相关的有害空气污染物的排放。在这项工作中,针对有害污染物(TREM-HAP)的线源运输排放模型已经开发了新版本。实施了苯,1,3-丁二烯,甲醛,乙醛,丙烯醛,萘以及颗粒物(PM2.5)的排放因子,并对该模型进行了扩展,以整合使用蒙特卡洛技术进行不确定性量化的概率方法。该方法已用于估计葡萄牙波尔图市区的道路交通排放量。自动计数系统提供的每小时交通流量计数用于表征车辆数量,车辆类别和不同路段的平均速度的时空变化。处理了两个夏季和两个冬季月份的数据,以获得不确定性分析所需的输入参数的概率密度函数。为了量化冷启动的过量排放,将日常出行的起点-目的地矩阵用作附加输入信息。对研究区域的道路交通产生的有害空气污染物的每日排放量进行了分析。与交通活动因子相关的排放估算的不确定性范围从小到公路上的丙烯醛和乙醛为22至+ 1.7%,考虑到城市街道行驶,则为1,33丁二烯的1,33至+ 70%。 。据估计,冷启动排放对每日总值的重要贡献,因此在苯的情况下达到了45%。最终城市排放清单中运输活动数据的不确定性突出了最重要的参数,并揭示了排放量化对输入数据的不同敏感性。这项工作中介绍的方法允许开发复杂城市地区中具有高时空分辨率的危险空气污染物排放清单,这是空气质量建模和暴露研究所需的,并且可以用作决策支持工具。

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