Abstract Particulate matter (PM) remains as one of the most relevant air-quality concerns in urban environments. The Berlin agglomeration area is still affected by exceedances of the daily limit value of the PM concentration, especially during wintertime PM episodes. In this study, we present test-case studies with the LOTOS-EUROS CTM to improve the representation of PM episodes in the Berlin agglomeration area. A variety of simulations were compared for two winter episodes characterized by cold stagnant conditions, using different meteorological input data (from the European Centre for Medium Weather Forecast (ECMWF) and the Consortium for Small-Scale Modelling-Climate Limited-area Modelling (COSMO-CLM)) and horizontal and vertical resolutions of the LOTOS-EUROS CTM. The LOTOS-EUROS CTM indicates too high mixing from the planetary boundary layer (PBL) to higher layers, leading to an underestimation of the PM mass concentration in the Berlin agglomeration. As major impact factor the mixing layer height (MLH) can be identified. Through applying the COSMO-CLM model the meteorological representation of the PBL and MLH can significantly be improved, whereas sensitivity studies only exhibit a small variation of the PBL meteorology and did not further improve the MLH. As the MLHs of both models are underestimated compared to observations and their derivation is questionable, we advise not to use this quantity any longer in CTMs. By contrast, applying a multi-level approach excluding the MLH, provides a considerable increase in the total PM mass concentration amount. The redistribution and increased nitrate and ammonium concentration can be mentioned as the main culprit. However, the best-fit simulations were obtained for the multi-level configuration fed by COSMO-CLM input data, additionally representing a more realistic urban increment.

中文翻译：

---

使用 LOTOS-EUROS CTM 对德国柏林集聚区 PM10 浓度事件的多气象比较

摘要 颗粒物 (PM) 仍然是城市环境中最相关的空气质量问题之一。柏林集聚区仍然受到 PM 浓度超标日的影响，尤其是在冬季 PM 发作期间。在这项研究中，我们展示了使用 LOTOS-EUROS CTM 的测试案例研究，以改善柏林集聚区 PM 事件的代表性。使用不同的气象输入数据（来自欧洲中期天气预报中心 (ECMWF) 和小规模建模-气候有限区域建模联盟 (COSMO- CLM)) 以及 LOTOS-EUROS CTM 的水平和垂直分辨率。LOTOS-EUROS CTM 表明从行星边界层 (PBL) 到更高层的混合太高，导致对柏林聚集体中 PM 质量浓度的低估。可以确定混合层高度 (MLH) 作为主要影响因素。通过应用 COSMO-CLM 模型，可以显着改善 PBL 和 MLH 的气象表征，而敏感性研究仅显示 PBL 气象的微小变化，并没有进一步改善 MLH。由于与观测值相比，两个模型的 MLH 都被低估了，而且它们的推导是有问题的，我们建议不要再在 CTM 中使用这个数量。相比之下，应用除 MLH 之外的多级方法可显着增加 PM 质量浓度总量。可以提到重新分配和增加硝酸盐和铵浓度是罪魁祸首。然而，由 COSMO-CLM 输入数据提供的多级配置获得了最佳拟合模拟，另外还代表了更现实的城市增量。