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Urban aerosol assessment and forecast: Coimbra case study
Atmospheric Pollution Research ( IF 4.5 ) Pub Date : 2020-04-18 , DOI: 10.1016/j.apr.2020.04.006
O. Tchepel , A. Monteiro , D. Dias , C. Gama , N. Pina , J.P. Rodrigues , M. Ferreira , A.I. Miranda

The objective of this study is to explore the existing services at a regional scale and study their applicability to the assessment and forecast of air quality at the urban scale. Two approaches were evaluated to characterize urban background pollution levels from the regional operational forecast: (i) Copernicus Atmosphere Monitoring Service (CAMS) and (ii) Chemical Transport Model CHIMERE from the national forecast system. The local contribution from road traffic was analysed using transportation (VISUM) -emission (QTraffic) - dispersion (ADMS-Roads) modelling chain with 10 m grid resolution. The methodology was applied to Coimbra city to estimate PM10 concentrations for the period of one year (2018). In order to validate the model outputs against the daily observations, the FAIRMODE Delta Tool was applied separately for regional and urban scale. The results obtained for Coimbra satisfy the modelling performance criteria. However, both approaches used to characterize background concentrations underestimate PM10 levels. The modelling bias at urban traffic station is about 6 μg m−3 for annual mean concentration. Local highest contribution of road traffic to PM10 annual mean obtained with high grid resolution (10 m) achieves 22 μg m−3. Spatial distribution of PM10 concentrations highlights the limitations to characterize urban hot spots based on the measurements from only one traffic station available within the study area and used to validate the urban scale model.



中文翻译:

城市气溶胶评估与预报:科英布拉案例研究

这项研究的目的是在区域范围内探索现有服务,并研究其在城市范围内对空气质量进行评估和预测的适用性。评估了两种方法以根据区域运营预测来表征城市背景污染水平:(i)哥白尼大气监测服务(CAMS)和(ii)国家预测系统中的化学运输模型CHIMERE。使用交通(VISUM)-排放(QTraffic)-离散(ADMS-Roads)建模链(网格分辨率为10 m)分析了道路交通对当地的贡献。该方法已应用于科英布拉市以估算PM 10一年(2018)的浓度。为了对照日常观察验证模型输出,FAIRMODE Delta工具分别用于区域和城市规模。Coimbra获得的结果满足建模性能标准。但是,用于表征背景浓度的两种方法都低估了PM 10的水平。对于年平均浓度,城市交通站的建模偏差约为6μgm -3。在高分辨率(10 m)下获得的道路交通对PM 10年均值的局部最高贡献达到22μgm -3。PM 10的空间分布 浓度突显了基于研究区域内仅有的一个交通站点的测量结果来表征城市热点的局限性,并用于验证城市规模模型。

更新日期:2020-04-18
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