Predicting air quality of Dhaka and Sylhet divisions in Bangladesh: a time series modeling approach

Md Mazharul Islam; Mowshumi Sharmin; Faroque Ahmed

doi:10.1007/s11869-020-00823-9

Predicting air quality of Dhaka and Sylhet divisions in Bangladesh: a time series modeling approach

Md Mazharul Islam^*, Mowshumi Sharmin, Faroque Ahmed

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

25 Citations (Scopus)

Abstract

Air pollution has emerged as one of the major public health threats. In recent years, Bangladesh has ranked among top air polluted countries around the globe. Air quality in Bangladesh is measured on daily basis using national standards of five pollutants—NO₂, CO, Ozone (O₃), SO₂, and particulate matter (PM_2.5 and PM₁₀) and presented as indexed value ranged from 0 to 500 which is further classified from good to extremely unhealthy. In this study, we have applied Seasonal Autoregressive Integrated Moving Average (SARIMA) model to forecast weekly air quality of Dhaka and Sylhet divisions in Bangladesh. Our study reveals the existence of seasonal pattern of the air quality and suggests extremely unhealthy and very unhealthy air in January–March 2020. Therefore, policymaker should address this period as the air quality directly influences public health.

Original language	English
Pages (from-to)	607-615
Number of pages	9
Journal	Air Quality, Atmosphere and Health
Volume	13
Issue number	5
DOIs	https://doi.org/10.1007/s11869-020-00823-9
Publication status	Published - May 1 2020
Externally published	Yes

Keywords

Air pollution
Air quality
Bangladesh
SARIMA model
Time series modeling

ASJC Scopus subject areas

Pollution
Atmospheric Science
Management, Monitoring, Policy and Law
Health, Toxicology and Mutagenesis

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/s11869-020-00823-9

Cite this

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abstract = "Air pollution has emerged as one of the major public health threats. In recent years, Bangladesh has ranked among top air polluted countries around the globe. Air quality in Bangladesh is measured on daily basis using national standards of five pollutants—NO2, CO, Ozone (O3), SO2, and particulate matter (PM2.5 and PM10) and presented as indexed value ranged from 0 to 500 which is further classified from good to extremely unhealthy. In this study, we have applied Seasonal Autoregressive Integrated Moving Average (SARIMA) model to forecast weekly air quality of Dhaka and Sylhet divisions in Bangladesh. Our study reveals the existence of seasonal pattern of the air quality and suggests extremely unhealthy and very unhealthy air in January–March 2020. Therefore, policymaker should address this period as the air quality directly influences public health.",

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AU - Islam, Md Mazharul

AU - Sharmin, Mowshumi

AU - Ahmed, Faroque

PY - 2020/5/1

Y1 - 2020/5/1

N2 - Air pollution has emerged as one of the major public health threats. In recent years, Bangladesh has ranked among top air polluted countries around the globe. Air quality in Bangladesh is measured on daily basis using national standards of five pollutants—NO2, CO, Ozone (O3), SO2, and particulate matter (PM2.5 and PM10) and presented as indexed value ranged from 0 to 500 which is further classified from good to extremely unhealthy. In this study, we have applied Seasonal Autoregressive Integrated Moving Average (SARIMA) model to forecast weekly air quality of Dhaka and Sylhet divisions in Bangladesh. Our study reveals the existence of seasonal pattern of the air quality and suggests extremely unhealthy and very unhealthy air in January–March 2020. Therefore, policymaker should address this period as the air quality directly influences public health.

AB - Air pollution has emerged as one of the major public health threats. In recent years, Bangladesh has ranked among top air polluted countries around the globe. Air quality in Bangladesh is measured on daily basis using national standards of five pollutants—NO2, CO, Ozone (O3), SO2, and particulate matter (PM2.5 and PM10) and presented as indexed value ranged from 0 to 500 which is further classified from good to extremely unhealthy. In this study, we have applied Seasonal Autoregressive Integrated Moving Average (SARIMA) model to forecast weekly air quality of Dhaka and Sylhet divisions in Bangladesh. Our study reveals the existence of seasonal pattern of the air quality and suggests extremely unhealthy and very unhealthy air in January–March 2020. Therefore, policymaker should address this period as the air quality directly influences public health.

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KW - Air quality

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KW - SARIMA model

KW - Time series modeling

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Predicting air quality of Dhaka and Sylhet divisions in Bangladesh: a time series modeling approach

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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