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Implementation of road dust resuspension in air quality simulations of particulate matter in Madrid (Spain)

机译:在马德里(西班牙)的颗粒物空气质量模拟中实施道路除尘技术

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摘要

An evaluation of the concentration levels of Particulate Matter (PM) was carried out in Madrid (Spain) by introducing the emissions from road dust resuspension. Road dust resuspension emission factors (EF) for different types of vehicles were calculated from EPA-AP42, a global resuspension factor of 0.097 g veh−1 km−1 as described in Amato et al. (2010) and a rain-dependent correction factor. With these resuspension EFs, a simulation at street canyon level was performed with the OSPM model without rainfall. Subsequently, a simulation using the CMAQ model was implemented adding resuspension emissions affected by the rain. These data were compared with monitored data obtained from air quality stations. OSPM model simulations with resuspension EFs but without the effect of rainfall improve the PM estimates in about 20 μg m−3 compared to the simulation with default EFs. Total emissions were calculated by adding the emissions estimated with resuspension EFs to the default PM emissions to be used by CMAQ. For the study in the Madrid Area, resuspension emissions are approximately of the same order of magnitude as inventoried emissions. On a monthly scale, rain effects are negligible for resuspension emissions due to the dry weather conditions of Spain. With the exception of April and May, the decrease in resuspension emissions is not >3%. The predicted PM10 concentration increases up to 9 μg m−3 on annual average for each station compared to the same scenario without resuspension. However, in both cases, PM10 estimates with resuspension are still underestimating observations. It should be noted that although that accounting for resuspension improves the quality of model predictions, other PM sources (e.g., Saharan dust) were not considered in this study.
机译:在马德里(西班牙),通过引入道路扬尘的悬浮物,对颗粒物(PM)的浓度水平进行了评估。根据EPA-AP42计算出不同类型车辆的道路扬尘排放因子(EF),如Amato等人所述,其总悬浮因子为0.097 g veh-1 km-1。 (2010年)和取决于降雨的校正因子。使用这些重悬浮EF,使用OSPM模型在没有降雨的情况下在街道峡谷级别进行了仿真。随后,使用CMAQ模型进行了模拟,增加了受雨水影响的悬浮悬浮物。这些数据与从空气质量站获得的监测数据进行了比较。与具有默认EF的模拟相比,使用重悬浮EF但不受降雨影响的OSPM模型模拟将PM估计值提高了约20μgm-3。总排放量是通过将重悬EF估算的排放量与CMAQ使用的默认PM排放量相加得出的。对于马德里地区的研究,悬浮排放量与清单排放量的数量级大致相同。在每月范围内,由于西班牙干燥的天气条件,降雨对悬浮排放的影响可以忽略不计。除4月和5月外,悬浮排放物的减少量不超过3%。与没有重新悬浮的相同情况相比,每个站点的预测PM10浓度平均每年增加至9μgm-3。但是,在这两种情况下,PM10的重估估计仍然低估了观测值。应该注意的是,尽管考虑到重悬可以提高模型预测的质量,但在本研究中未考虑其他PM源(例如,撒哈拉尘埃)。

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