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Influence of anthropogenic emission inventories on simulations of air quality in China during winter and summer 2010

机译:人为排放清单对2010年冬季和夏季中国空气质量模拟的影响

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We apply the regional chemistry-transport model WRF-Chem to investigate the air pollution characteristics in three Chinese metropolitan areas (Beijing, Shanghai and Guangzhou) and assess the model performance in wintertime (January 2010) and summertime (July 2010) conditions. Three simulations utilizing the HTAPv2, REASv2 and MACCity anthropogenic emission inventories are conducted and compared with satellite and ground-based measurements to assess the sensitivity of the model predictions to anthropogenic emissions. Model-predicted surface meteorological fields are overall in good agreement with surface observations. However, the model tends to overestimate maximum surface wind speed, a feature also found in previous WRF-Chem modelling studies. Large discrepancies between the three emission inventories are found, specifically in the spatial distribution and the magnitude of the emissions (e.g. over 98%, 86% and 85% differences in some regions for carbon monoxide (CO), nitrogen oxide (NO) and organic carbon (OC) emissions, respectively). As a result, we find large differences between the simulations. When compared to satellite and surface observations, the HTAPv2-and REASv2-based simulations better reproduce the magnitude and spatial patterns of CO total columns and NO2tropospheric columns derived from MOPITTv6 and GOME2 satellite observations, respectively. The simulations satisfactorily reproduce the air pollution characteristics in January 2010 as observed at surface monitoring stations in Beijing and Shanghai. The HTAPv2-based simulation better captures the pollution episode that occurred in Beijing in mid-January 2010, which is found to be related to a combination of different meteorological factors that led to the build-up of pollution. The high photochemical activity and convective turbulence in July 2010, in addition to differences in the emissions used, led to more pronounced differences between the simulations and lower statistical skills in particular for trace gases.This study shows that a considerable part of uncertainties in air quality model predictions for China can be attributed to uncertainties in current anthropogenic emission inventories. It highlights the need for more accurate and highly resolved emissions in order to improve the accuracy of model predictions. However, this study reveals that in some cases, model-observation discrepancies cannot be attributed only to inaccuracies in the emissions. For example, we found that regardless of the adopted emissions, all of the simulations fail to capture the temporal variability of particulate matter in Guangzhou during January 2010, indicating that factors other than emissions have a considerable influence on the atmospheric composition in this region. This work shows that inaccuracies in the predicted meteorological parameters (e.g. wind speed/direction, relative humidity, etc.) significantly affect the model performance, as found for example in the model predictions for Shanghai for July 2010, which show high and abrupt increases of NOx and particulates due to rapid decreases in wind speed in the model.
机译:我们使用区域化学运输模型WRF-Chem来调查中国三个大都市区(北京,上海和广州)的空气污染特征,并评估冬季(2010年1月)和夏季(2010年7月)条件下的模型性能。进行了三个使用HTAPv2,REASv2和MACCity人为排放清单的模拟,并将其与卫星和地面测量结果进行了比较,以评估模型预测对人为排放的敏感性。模型预测的地面气象领域总体上与地面观测非常吻合。但是,该模型往往高估了最大表面风速,这在以前的WRF-Chem建模研究中也发现过。发现三个排放清单之间存在较大差异,特别是在空间分布和排放量方面(例如,某些地区一氧化碳(CO),氮氧化物(NO)和有机物的差异超过98%,86%和85%)碳排放量)。结果,我们发现模拟之间存在很大差异。与卫星和地面观测相比,基于HTAPv2和REASv2的模拟分别更好地重现了从MOPITTv6和GOME2卫星观测获得的CO总柱和NO2对流层柱的大小和空间模式。该模拟令人满意地再现了2010年1月在北京和上海的地面监测站观察到的空气污染特征。基于HTAPv2的模拟可以更好地捕获2010年1月中旬在北京发生的污染事件,这被发现与导致污染累积的各种气象因素的组合有关。除了使用的排放物不同外,2010年7月的高光化学活性和对流湍流还导致模拟之间的差异更加明显,特别是对于痕量气体的统计能力较低。这项研究表明,空气质量中的很大一部分不确定性中国的模型预测可以归因于当前人为排放清单的不确定性。它强调了需要更准确和高度解析的排放量以提高模型预测的准确性。但是,这项研究表明,在某些情况下,模型观察的差异不能仅归因于排放量的不准确。例如,我们发现,无论采用何种排放,所有模拟都无法捕获2010年1月广州地区颗粒物的时间变化,这表明排放以外的其他因素对该地区的大气成分有很大影响。这项工作表明,预测的气象参数(例如风速/方向,相对湿度等)的不准确性会严重影响模型的性能,例如在2010年7月对上海的模型预测中发现的结果表明,该值的高而突然增加在模型中,由于风速的迅速降低而导致的NOx和颗粒物。

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