Department of Chemical & Environmental Engineering, Universidad Politécnica de Madrid (UPM), Madrid, Spain; Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ingeniería en Mecánica y Ciencias de la Producción, Guayaquil, Ecuador.
Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ingeniería en Mecánica y Ciencias de la Producción, Guayaquil, Ecuador; Instituto Superior Tecnológico Benjamín Rosales Pareja, Guayaquil, Ecuador.
Sci Total Environ. 2022 Nov 20;848:157664. doi: 10.1016/j.scitotenv.2022.157664. Epub 2022 Jul 28.
Emissions from mobile sources have become a major concern for health, environmental sustainability and climate change and high-resolution inventories are needed to support the design and assessment of abatement measures in urban areas. This study addresses the development of a traffic emissions inventory for Guayaquil, the second largest city in Ecuador, using the International Vehicle Emissions Model (IVE). Emissions are allocated with a spatial resolution of 1 km × 1 km and a temporal resolution of 1 h using a top-down methodology. This application combines traffic statistics already available in the city with the data from a field campaign to characterize vehicle fleet composition and activity patterns. The estimated annual emissions for the city were 237.1 kt of CO, 46.4 kt of NOx, 28.5 kt of VOC, 7.7 kt of PM, 0.70 kt of SO and 4549.7 kt of CO. 92.3 % of CO and 85.4 % of VOC were emitted by light gasoline vehicles, including private passenger vehicles and taxis, which represents 68.6 % and 8.8 %, respectively of the total fleet and contributes 52 % and 22 % of the total vehicle kilometer traveled (VKT), respectively. 48.9 % of NOx and 82 % of PM were emitted by the bus fleet although buses only represent 7.5 % of the total fleet and contribute 10.6 % of total VKT in the city. 41.1 % and 36.5 % of CO were emitted by buses and private vehicles, respectively. Even though, the average age of the fleet is below 10 years, the fleet in Guayaquil presents outdated emission standards and high emission factors. We found the higher emission rates in dense populated areas are associated to secondary roads. There is not much variability of emissions between months, but the typical daily pattern of emissions shows a peak in the morning and another in the afternoon.
移动源排放物已成为健康、环境可持续性和气候变化的主要关注点,因此需要高分辨率清单来支持城市减污措施的设计和评估。本研究利用国际车辆排放模型(IVE),针对厄瓜多尔第二大城市瓜亚基尔,开发了一个交通排放清单。排放物以 1km×1km 的空间分辨率和 1h 的时间分辨率进行分配,采用自上而下的方法。该应用将城市中已有的交通统计数据与现场调查数据相结合,以确定车辆车队组成和活动模式。该市的年排放量估计为 237.1 千吨 CO、46.4 千吨 NOx、28.5 千吨 VOC、7.7 千吨 PM、0.70 千吨 SO 和 4549.7 千吨 CO。92.3%的 CO 和 85.4%的 VOC 由轻型汽油车排放,包括私人乘用车和出租车,分别占车队总数的 68.6%和 8.8%,占总行驶里程的 52%和 22%。48.9%的 NOx 和 82%的 PM 由公共汽车车队排放,尽管公共汽车仅占车队总数的 7.5%,但在该市占总行驶里程的 10.6%。41.1%和 36.5%的 CO 分别由公共汽车和私人车辆排放。尽管车队的平均车龄低于 10 年,但瓜亚基尔的车队仍采用过时的排放标准和高排放系数。我们发现,人口密集地区的排放率较高与次要道路有关。各月份之间的排放量变化不大,但典型的日排放模式显示出上午和下午的峰值。