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基于活动的交通模型对空气质量建模的贡献:ALBATROSS-AURORA模型链的验证

The contribution of activity-based transport models to air quality modelling: a validation of the ALBATROSS-AURORA model chain.

作者信息

Beckx Carolien, Int Panis Luc, Van De Vel Karen, Arentze Theo, Lefebvre Wouter, Janssens Davy, Wets Geert

机构信息

Flemish Institute for Technological Research, Boeretang 200, 2400 Mol, Belgium.

出版信息

Sci Total Environ. 2009 Jun 1;407(12):3814-22. doi: 10.1016/j.scitotenv.2009.03.015. Epub 2009 Apr 3.

Abstract

The potential advantages of using activity-based transport models for air quality purposes have been recognized for a long time but models that have been developed along these lines are still scarce. In this paper we demonstrate that an activity-based model provides useful information for predicting hourly ambient pollutant concentrations. For this purpose, the traffic emissions obtained in a previous application of the activity-based model ALBATROSS were used as input for the AURORA air quality model to predict hourly concentrations of NO(2), PM(10) and O(3) in the Netherlands. Predicted concentrations were compared with measured concentrations at 37 monitoring stations from the Dutch air quality monitoring network. A statistical analysis was performed to evaluate model performance for different pollutants, locations and time periods. Results confirm that modelled and measured concentrations present the same geographical and temporal variation. The overall index of agreement for the prediction of hourly pollutant concentrations amounted to 0.64, 0.75 and 0.57 for NO(2), O(3) and PM(10) respectively. Concerning the predictions for NO2, a major traffic pollutant, a more thorough analysis revealed that the ALBATROSS-AURORA model chain yielded better predictions near traffic locations than near background stations. Further, the model performed better in urban areas, on weekdays and during the day, consistent with the emission results obtained in a previous study. The results in this paper demonstrate the ability of the activity-based model to predict the contribution of traffic sources to local air pollution with sufficient accuracy and confirms the usefulness of activity-based transport models for air quality purposes. The fact that the ALBATROSS-AURORA chain provides reliable pollutant concentrations on hourly basis for the whole Netherlands instead of using only daily averages near traffic stations is a plus for future exposure studies aiming at more realistic exposure analyses and health impact assessments.

摘要

长期以来,人们已经认识到基于活动的交通模型在空气质量方面的潜在优势,但按照这些思路开发的模型仍然很少。在本文中,我们证明了基于活动的模型为预测每小时的环境污染物浓度提供了有用信息。为此,将基于活动的模型ALBATROSS先前应用中获得的交通排放作为AURORA空气质量模型的输入,以预测荷兰NO(2)、PM(10)和O(3)的每小时浓度。将预测浓度与荷兰空气质量监测网络中37个监测站的测量浓度进行比较。进行了统计分析,以评估模型在不同污染物、地点和时间段的性能。结果证实,建模浓度和测量浓度呈现出相同的地理和时间变化。每小时污染物浓度预测的总体一致性指数分别为NO(2) 0.64、O(3) 0.75和PM(10) 0.57。关于主要交通污染物NO2的预测,更深入的分析表明,ALBATROSS - AURORA模型链在交通地点附近的预测比在背景站附近更好。此外,该模型在城市地区、工作日和白天表现更好,这与先前研究中获得的排放结果一致。本文的结果证明了基于活动的模型能够以足够的准确性预测交通源对当地空气污染的贡献,并证实了基于活动的交通模型在空气质量方面的有用性。ALBATROSS - AURORA链能够为整个荷兰每小时提供可靠的污染物浓度,而不是仅使用交通站附近的日平均值,这对于未来旨在进行更现实的暴露分析和健康影响评估的暴露研究来说是一个优势。

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