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Instantaneous emissions models set in GIS for the TRANSIMS outputs

机译：在GIS中为TRANSIMS输出设置的瞬时排放模型

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A novel methodology that provides more detailed estimates of vehicular polluting emissions is offered, in order to contribute to the improvement and the precision of emission inventories of vehicle sources through the consideration of instantaneous speed changes or acceleration instead of average vehicular speeds. This paper presents the construction and application of an instantaneous emissions model designated hereunder as "Transims's Snapshots-Based Emissions", which is set on a Geographic Information System that incorporates instantaneous fuel consumption factors and fuel-based emission factors to attain highest resolution of both, spatial and temporal distribution of vehicular polluting emissions based on traffic simulation through cellular automata with TRANSIMS. This work was applied to the road network of the Mexico City Metropolitan Area as case study. The development of this powerful tool led to obtaining 86,400 maps of the spatial and temporal distribution of vehicular emissions per vehicle circulating on the road network, including the following pollutants: carbon monoxide and carbon dioxide, nitrogen oxides, total hydrocarbons, sulfur oxides, polycyclic aromatic hydrocarbons, black carbon, particles PM_(10) and PM_(2.5). The said maps allowed identification with highest level of detail, of the emissions and Hot-spots of fuel consumption. Also, the model permitted to obtain the emissions' longitudinal profiles of a given vehicle along its route. This study shows that the integration method of the polynomial regression models represents an opportunity for each city to develop more easily and openly its own regional emissions models without requiring deeper programming knowledge.
机译：提供一种新颖的方法，其提供对车辆污染排放的更详细的估计，以便通过考虑瞬时速度变化或加速度而不是平均车辆速度来促进车辆源排放清单的改进和精度。本文介绍了以下瞬时排放模型的构建和应用，该模型称为“基于Transims快照的排放”，该模型基于地理信息系统，该系统结合了瞬时燃料消耗因子和基于燃料的排放因子，以实现两者的最高分辨率，基于带有TRANSIMS的元胞自动机交通模拟的车辆污染排放的时空分布。作为案例研究，这项工作被应用于墨西哥城都市区的道路网络。这个强大工具的开发导致获得了在道路网络上循环行驶的每辆汽车的汽车排放时空分布的86,400张地图，包括以下污染物：一氧化碳和二氧化碳，氮氧化物，总碳氢化合物，硫氧化物，多环芳烃碳氢化合物，黑碳，颗粒PM_（10）和PM_（2.5）。所述地图允许以最高水平的细节来识别排放和燃料消耗的热点。同样，该模型允许获得沿给定车辆在其路线上的排放物的纵向轮廓。这项研究表明，多项式回归模型的积分方法为每个城市提供了一个机会，使他们可以更轻松，更开放地开发自己的区域排放模型，而无需更多的编程知识。

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