University of Aveiro, Centre for Mechanical Technology and Automation (TEMA), Department of Mechanical Engineering, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal.
University of Aveiro, Centre for Mechanical Technology and Automation (TEMA), Department of Mechanical Engineering, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal.
Sci Total Environ. 2014 Feb 1;470-471:127-37. doi: 10.1016/j.scitotenv.2013.09.042. Epub 2013 Oct 12.
The accuracy and precision of air quality models are usually associated with the emission inventories. Thus, in order to assess if there are any improvements on air quality regional simulations using detailed methodology of road traffic emission estimation, a regional air quality modelling system was applied. For this purpose, a combination of top-down and bottom-up approaches was used to build an emission inventory. To estimate the road traffic emissions, the bottom-up approach was applied using an instantaneous emission model (Vehicle Specific Power - VSP methodology), and an average emission model (CORINAIR methodology), while for the remaining activity sectors the top-down approach was used. Weather Research and Forecasting (WRF) and Comprehensive Air quality (CAMx) models were selected to assess two emission scenarios: (i) scenario 1, which includes the emissions from the top-down approach; and (ii) scenario 2, which includes the emissions resulting from integration of top-down and bottom-up approaches. The results show higher emission values for PM10, NOx and HC, for scenario 1, and an inverse behaviour to CO. The highest differences between these scenarios were observed for PM10 and HC, about 55% and 75% higher (respectively for each pollutant) than emissions provided by scenario 2. This scenario gives better results for PM10, CO and O3. For NO2 concentrations better results were obtained with scenario 1. Thus, the results obtained suggest that with the combination of the top-down and bottom-up approaches to emission estimation several improvements in the air quality results can be achieved, mainly for PM10, CO and O3.
空气质量模型的准确性和精密度通常与排放清单有关。因此，为了评估使用道路交通排放估算详细方法是否可以改善区域空气质量模拟，应用了区域空气质量模拟系统。为此，采用自上而下和自下而上的方法相结合来建立排放清单。为了估算道路交通排放，采用自下而上的方法，使用瞬时排放模型（车辆特定功率-VSP 方法）和平均排放模型（CORINAIR 方法），而对于其余活动部门，则采用自上而下的方法。选择天气研究和预报（WRF）和综合空气质量（CAMx）模型来评估两种排放情景：（i）情景 1，其中包括自上而下方法的排放；和（ii）情景 2，其中包括自上而下和自下而上方法整合的排放。结果表明，PM10、NOx 和 HC 的排放值在情景 1 中更高，而 CO 的排放值则相反。这些情景之间的最大差异观察到 PM10 和 HC，分别比情景 2 提供的排放高 55%和 75%（对于每种污染物）。该情景对 PM10、CO 和 O3 的结果更好。对于 NO2 浓度，情景 1 得到了更好的结果。因此，所得结果表明，通过自上而下和自下而上的方法相结合进行排放估算，可以在空气质量结果方面实现多项改进，主要是针对 PM10、CO 和 O3。
