Air pollution changes in urban and non-urban areas depend highly on the seasons and winds. However, it is scant to evaluate the effects of seasonality on air pollution, such as particulate matter (PM) using remote sensing data in Iran. Therefore, investigating the impacts of seasonal changes on PM10 is imperative to mitigate its adverse effect. Local Climate Zone (LCZ) is a new approach in classification of urban land use and climate zones to estimate seasonal PM10 changes in urban regions. In this article, seasonal PM10 distribution changes were evaluated in terms of seasonality and spatial LCZ distribution in Tehran city. Machine learning and Random Forest algorithm were used to classify LCZs and Saraswat algorithm was used for evaluating spatial PM10 distribution. The results showed that seasonality could significantly affect PM10 levels in Tehran region. PM10 levels in autumn and winter are much higher than that in spring and summer. There was the highest PM10 level due to a low average precipitation in autumn while the lowest levels in summer. It is also found that the summer-autumn change caused substantial increases in all LCZs except for LCZ G of large water area. The largest percentage of increases in Tehran city was related to change of summer to autumn (93.9 %) while the largest decrease was in winter to spring (84.6 %). It was also found that PM10 level changes more in the urban LCZs than in the non-urban LCZs.

中文翻译：

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基于空间局部气候带分布的室外 PM10 季节性变化


城市和非城市地区的空气污染变化在很大程度上取决于季节和风。然而，使用伊朗的遥感数据评估季节性对空气污染的影响，例如颗粒物 （PM），这一点很少。因此，研究季节性变化对 PM10 的影响对于减轻其不利影响势在必行。局部气候区 （LCZ） 是一种对城市土地利用和气候区进行分类的新方法，用于估计城市地区的季节性 PM10 变化。本文从季节性和空间 LCZ 分布的角度评估了德黑兰市 PM10 的季节性分布变化。机器学习和随机森林算法用于对 LCZ 进行分类，Saraswat 算法用于评估空间 PM10 分布。结果表明，季节性会显著影响德黑兰地区的 PM10 水平。秋冬季的 PM10 水平远高于春季和夏季。由于秋季平均降水量低，PM10 水平最高，而夏季最低。研究还发现，夏秋季变化导致除大水域的 LCZ G 外的所有 LCZ 均大幅增加。德黑兰市增长的最大百分比与夏季到秋季的变化有关 （93.9 %），而冬季到春季的下降幅度最大 （84.6 %）。研究还发现，城市 LCZ 的 PM10 水平变化大于非城市 LCZ。