The University of Southampton
University of Southampton Institutional Repository
Warning ePrints Soton is experiencing an issue with some file downloads not being available. We are working hard to fix this. Please bear with us.

Estimation and forecasting of PM10 air pollution in Ankara via time series and harmonic regressions

Estimation and forecasting of PM10 air pollution in Ankara via time series and harmonic regressions
Estimation and forecasting of PM10 air pollution in Ankara via time series and harmonic regressions
In this study, monthly particulate matter (PM10) values in Ankara (39.9334° N, 32.8597° E) from January 1993 to December 2017 are examined. The PM10 are those thoracic particles whose aerodynamic diameter is less than 10 μm (micrometers), and it is of critical health importance due to the penetrability to the lower airways. As an alternative to classical unit root tests, a unit root test primarily based on periodograms is introduced owing to its advantages over alternatives. After examining the stationarity of the series through periodogram-based test as well as its standard rivals, periodic components in the series are examined and it is observed that the series has both periodic and seasonal components. These components are modeled, using the inherent dynamics of a time series alone, within a trigonometric harmonic regression setup, eventually yielding the forecast values for 2018 that turns out to be superior to those obtained by means of ARIMA (autoregressive integrated moving average). This is a striking result since the modeling framework requires no assumptions, no parameter estimations except for the variance of the white noise series, no simulations of the power of tests, no adjustments of test statistics with respect to sample size and no preliminary work as to independent variable which is simply time, i.e., the period of forecast.
Air pollution, Forecasting, Harmonic regression, PM concentration, Periodogram, Time series analysis
1735-1472
3677-3690
Okkaoglu, Yasin
2e573ed6-84ea-45de-b260-6db0394cdb65
Akdi, Y.
94d4f5bc-cf2f-4caa-ac77-962ab120f49d
Golveren, E.
c2a3f67c-6e9f-4283-aea8-6f759ece6fa0
Yucel, M.
3647bb14-2489-4da2-9e97-d86f8db0bd8a
Okkaoglu, Yasin
2e573ed6-84ea-45de-b260-6db0394cdb65
Akdi, Y.
94d4f5bc-cf2f-4caa-ac77-962ab120f49d
Golveren, E.
c2a3f67c-6e9f-4283-aea8-6f759ece6fa0
Yucel, M.
3647bb14-2489-4da2-9e97-d86f8db0bd8a

Okkaoglu, Yasin, Akdi, Y., Golveren, E. and Yucel, M. (2020) Estimation and forecasting of PM10 air pollution in Ankara via time series and harmonic regressions. International Journal of Environmental Science and Technology, 17 (8), 3677-3690. (doi:10.1007/s13762-020-02705-0).

Record type: Article

Abstract

In this study, monthly particulate matter (PM10) values in Ankara (39.9334° N, 32.8597° E) from January 1993 to December 2017 are examined. The PM10 are those thoracic particles whose aerodynamic diameter is less than 10 μm (micrometers), and it is of critical health importance due to the penetrability to the lower airways. As an alternative to classical unit root tests, a unit root test primarily based on periodograms is introduced owing to its advantages over alternatives. After examining the stationarity of the series through periodogram-based test as well as its standard rivals, periodic components in the series are examined and it is observed that the series has both periodic and seasonal components. These components are modeled, using the inherent dynamics of a time series alone, within a trigonometric harmonic regression setup, eventually yielding the forecast values for 2018 that turns out to be superior to those obtained by means of ARIMA (autoregressive integrated moving average). This is a striking result since the modeling framework requires no assumptions, no parameter estimations except for the variance of the white noise series, no simulations of the power of tests, no adjustments of test statistics with respect to sample size and no preliminary work as to independent variable which is simply time, i.e., the period of forecast.

This record has no associated files available for download.

More information

Accepted/In Press date: 6 March 2020
e-pub ahead of print date: 20 March 2020
Keywords: Air pollution, Forecasting, Harmonic regression, PM concentration, Periodogram, Time series analysis

Identifiers

Local EPrints ID: 438521
URI: http://eprints.soton.ac.uk/id/eprint/438521
ISSN: 1735-1472
PURE UUID: 2376ef72-e220-40bb-839f-4d74e512aa4a

Catalogue record

Date deposited: 12 Mar 2020 17:33
Last modified: 25 Nov 2021 19:30

Export record

Altmetrics

Contributors

Author: Yasin Okkaoglu
Author: Y. Akdi
Author: E. Golveren
Author: M. Yucel

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×