Statistical Methods to Forecast Air Quality in Taipa Ambient and Taipa Residential of Macao

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Abstract

Air pollution is a major concern issue on Macao since the concentration levels of several of the most common pollutants are frequently above the internationally recommended values. The low air quality episodes impacts on human health paired with highly populated urban areas are important motivations to develop forecast methodologies in order to anticipate pollution episodes, allowing establishing warnings to the local community to take precautionary measures and avoid outdoor activities during this period. Using statistical methods (multiple linear regression (MLR) and classification and regression tree (CART) analysis) we were able to develop forecasting models for the main pollutants (NO2, PM2.5, and O3) enabling us to know the next day concentrations with a good skill, translated by high coefficients of determination (0.82–0.90) on a 95% confidence level. The model development was based on six years of historical data, 2013 to 2018, consisting of surface and upper-air meteorological observations and surface air quality observations. The year of 2019 was used for model validation. From an initially large group of meteorological and air quality variables only a few were identified as significant dependent variables in the model. The selected meteorological variables included geopotential height, relative humidity and air temperature at different altitude levels and atmospheric stability characterization parameters. The air quality predictors used included recent past hourly levels of mean concentrations for NO2 and PM2.5 and maximum concentrations for O3. The application of the obtained models provides the expected daily mean concentrations for NO2 and PM2.5 and maximum hourly concentrations O3 for the next day in Taipa Ambient air quality monitoring stations. The described methodology is now operational, in Macao, since 2020.

Original languageEnglish
Title of host publicationAir Pollution Modeling and its Application XXVII
EditorsClemens Mensink, Volker Matthias
Place of PublicationBerlin, Heidelberg
PublisherSpringer
Pages167-173
Number of pages7
ISBN (Electronic)978-3-662-63760-9
ISBN (Print)978-3-662-63759-3
DOIs
Publication statusPublished - 2021
Event37th International Technical Meeting on Air Pollution Modeling and its Application, ITM 2019 - Hamburg, Germany
Duration: 23 Sep 201927 Sep 2019

Publication series

NameSpringer Proceedings in Complexity
PublisherSpringer
ISSN (Print)2213-8684
ISSN (Electronic)2213-8692

Conference

Conference37th International Technical Meeting on Air Pollution Modeling and its Application, ITM 2019
Country/TerritoryGermany
CityHamburg
Period23/09/1927/09/19

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