Concern about air-quality in urban areas has led to the implementation of Low Emission Zones as one of many other initiatives to control it. Recently in Spain, the enactment of a law made this mandatory for cities with a population larger than 50k inhabitants. The delimitation of these areas is not without controversy because of possible negative economic and social impacts. Therefore, clear assessments of how these initiatives decrease pollutant concentrations are to be provided. Madrid Central is a major initiative of Madrid city council for reducing motor traffic and the associated air pollution in the city centre. This Low Emission Zone starts at the end of 2018, but the first fully-operational period corresponds to the second quarter of 2019. In this work, a methodology based on the Gaussian Process to analyse the evolution of Nitrogen Dioxide inside Madrid Central is undertaken. A Gaussian Process is a stochastic process suitable for interpretable model selection and predictions. Due to its probabilistic nature it provides error estimation at predictions. After the activation of Madrid Central, a relevant reduction of Nitrogen Dioxide has been observed. However, the role of the meteorology during this period must be ascertained to correctly evaluate the role of the activation of the Low Emission Zone against a prone weather. In this work, a model based on the Gaussian Process is trained with meteorological information to predict the concentration of Nitrogen Dioxide at Madrid Central, $[NO_{2}]$. This probabilistic description allows extracting statistical information on the reduction affected by the meteorological scenario and separately by the Madrid Central activation.

中文翻译：

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基于高斯过程的马德里中部低排放区二氧化氮分析

对城市地区空气质量的担忧导致低排放区的实施，作为控制空气质量的其他举措之一。最近，西班牙颁布了一项法律，要求人口超过 5 万的城市强制执行此规定。由于可能产生负面的经济和社会影响，这些区域的划界并非没有争议。因此，需要对这些举措如何降低污染物浓度进行明确的评估。马德里中心是马德里市议会的一项重大举措，旨在减少市中心的机动车交通和相关的空气污染。该低排放区于 2018 年底开始，但第一个全面运行期对应于 2019 年第二季度。在这项工作中，采用了一种基于高斯过程的方法来分析马德里市中心内二氧化氮的演变。高斯过程是一种适合可解释的模型选择和预测的随机过程。由于其概率性质，它提供了预测时的误差估计。马德里中心启用后，观察到二氧化氮相应减少。然而，必须确定这一时期气象的作用，以正确评估低排放区激活对易发天气的作用。在这项工作中，基于高斯过程的模型通过气象信息进行训练，以预测马德里中心 $[NO_{2}]$ 的二氧化氮浓度。这种概率描述允许提取有关气象情景和马德里中央激活影响的减少的统计信息。