This paper examines the statistical properties of daily PM₁₀ in eight European capitals (Amsterdam, Berlin, Brussels, Helsinki, London, Luxembourg, Madrid and Paris) over the period 2014–2020 by applying a fractional integration framework; this is more general than the standard approach based on the classical dichotomy between I(0) stationary and I(1) non-stationary series used in most other studies on air pollutants. All series are found to be characterised by long memory and fractional integration, with orders of integration in the range (0, 1), which implies that mean reversion occurs and shocks do not have permanent effects. Persistence is the highest in the case of Brussels, Amsterdam and London. The presence of negative trends in Brussels, Paris and Berlin indicates some degree of success in reducing pollution in these capitals.

本文研究了每日PM ₁₀的统计特性通过应用部分整合框架，在2014-2020年期间在八个欧洲首都（阿姆斯特丹，柏林，布鲁塞尔，赫尔辛基，伦敦，卢森堡，马德里和巴黎）开展业务；这比在大多数其他空气污染物研究中使用的基于I（0）平稳和I（1）非平稳序列之间的经典二分法的标准方法更为通用。发现所有系列的特征都在于长记忆和分数积分，积分阶数在（0，1）范围内，这意味着发生均值反转并且电击不会产生永久性影响。在布鲁塞尔，阿姆斯特丹和伦敦，持久性最高。布鲁塞尔，巴黎和柏林的消极趋势表明，这些首都在减少污染方面取得了一定程度的成功。