Bermejo, L. (Lorenzo)

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    Time trends and persistence in PM2.5 in 20 megacities: evidence for the time period 2018-2020
    (Springer, 2022) Bermejo, L. (Lorenzo); Río, M. (Marta) del; Gil-Alana, L.A. (Luis A.)
    The degree of persistence in daily data for PM2.5 in 20 relevant megacities such as Bangkok, Beijing, Mumbai, Calcutta, Canton, Dhaka, Delhi, Jakarta, London, Los Angeles, Mexico City, Moscow, New York, Osaka. Paris, Sao Paulo, Seoul, Shanghai, Tientsin, and Tokyo is examined in this work. The analysis developed is based on fractional integration techniques. Specifically, the differentiation parameter is used to measure the degree of persistence in the series under study, which collects data on daily measurements carried out from January 1, 2018, to December 31, 2020. The results obtained show that the estimated values for the differentiation parameter are restricted to the interval (0, 1) in all cases, which allows us to conclude that there is a mean reverting pattern and, therefore, transitory effects of shocks.
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    Atmospheric pollution in the ten most populated US cities. Evidence of persistence
    (Elsevier, 2021) Bermejo, L. (Lorenzo); Río, M. (Marta) del; Gil-Alana, L.A. (Luis A.)
    The degree of persistence in daily PM25 and O3 in the ten most populated US cities, namely New York, Los Angeles, Chicago, Houston, Phoenix, Philadelphia, San Antonio, San Diego, Dallas and San Jose is examined in this work. We employ a methodology based on fractional integration, using the order of integration as a measure of the degree of persistence. Using data for the time period from January 1, 2019 to December 31, 2020, our results indicate that fractional integration and long memory features are both present in all the examined cases, with the integration order of the series being constrained in the (0, 1) interval. Based on this, the estimation of the coefficients for the time trend produces results which are substantially different from those obtained under the I(0) assumption.