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Forecasting Hourly Ozone Concentration Using Functional Time Series Model—A Case Study in the Coastal Area of Bangladesh

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Abstract

Ozone has a significant impact on the environment. Atmospheric ozone concentration in coastal tourist areas now gains greater importance because tourists’ skin is directly exposed to sunlight. The current research provides the best prediction model to improve the prediction accuracy of ozone level for the coastal area of Bangladesh. The functional time series analysis (FTSA) is a direct extension of function-to-function regression model dealing with continuous curves. The proposed functional time series–based model was applied to the hourly ozone series observed over 92 days starting from March 2019 to May 2019 in the coastal area of Bangladesh. Descriptive measures were used to estimate the overall temporal patterns, and the functional principal component regression model (FPCR) was used to predict first day of monsoon season. In addition, functional autoregressive model (FAR(1)) was used to measure the impact of 1-h differences on next day’s ozone levels. Results of functional principal component regression reveal complex dynamic patterns of the ozone levels over hours and days. The first principal component primarily models afternoon-hour ozone levels, and the second principal component models the complex difference pattern between midnight to early morning, and the rest of the hourly ozone concentration. In addition, from FAR(1) model, our results confirm the moderate effect of ozone series of current day on the next day when the 1-h difference is observed (more specifically around office hours: 8 am to 17 pm). Finally, the highest peak was observed for forecasted series at 11 am. Intriguingly, we discovered that anticipated values perfectly fit observed values, resulting in the smallest forecasting error.

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Data could be available from the second author upon request and code could be available from the corresponding author upon request.

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Authors and Affiliations

  1. Department of Statistics, Jahangirnagar University, Savar, Dhaka, Bangladesh

    Azizur Rahman

  2. Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada

    Azizur Rahman

  3. Department of Geography and Environment, Jagannath University, Dhaka, Bangladesh

    N M Refat Nasher

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  1. Azizur Rahman
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Azizur Rahman wrote the main manuscript text, prepared figures and tables, and analyzed the data by writing R code. N. M. Refat reviewed the manuscript and contributed to the data collection section.

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Correspondence to Azizur Rahman.

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We used R [70], along with demography [71], ftsa [72], and forecast [73] packages.

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Rahman, A., Nasher, N.M.R. Forecasting Hourly Ozone Concentration Using Functional Time Series Model—A Case Study in the Coastal Area of Bangladesh. Environ Model Assess 29, 125–134 (2024). https://doi.org/10.1007/s10666-023-09928-8

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