A Review of Air Quality Modeling

Khaoula Karroum, Yijun Lin, Yao Yi Chiang, Yann Ben Maissa, Mohamed El Haziti, Anton Sokolov, Hervé Delbarre

Research output: Contribution to journalReview articlepeer-review

11 Scopus citations

Abstract

Air quality models (AQMs) are useful for studying various types of air pollutions and provide the possibility to reveal the contributors of air pollutants. Existing AQMs have been used in many scenarios having a variety of goals, e.g., focusing on some study areas and specific spatial units. Previous AQM reviews typically cover one of the forming elements of AQMs. In this review, we identify the role and relevance of every component for building AQMs, including (1) the existing techniques for building AQMs, (2) how the availability of the various types of datasets affects the performance, and (3) common validation methods. We present recommendations for building an AQM depending on the goal and the available datasets, pointing out their limitations and potentials. Based on more than 40 works on air quality, we concluded that the main utilized methods in air pollution estimation are land-use regression (LUR), machine learning, and hybrid methods. In addition, when incorporating LUR methods with traffic variables, it gives promising results; however, when using kriging or inverse distance weighting techniques, the monitoring stations measurements of air pollution data are enough to have good results. We aim to provide a short manual for people who want to build an AQM given the constraints at hands such as the availability of datasets and technical/computing resources.

Original languageEnglish (US)
Pages (from-to)287-300
Number of pages14
JournalMapan - Journal of Metrology Society of India
Volume35
Issue number2
DOIs
StatePublished - Jun 1 2020
Externally publishedYes

Bibliographical note

Funding Information:
This work was supported by the scholarship of Excellence from the National Center for Scientific and Technical Research (CNRST) of Morocco and Universit? du Littoral C?te d?Opale of Dunkerque, France. We would like to thank Atmo Hauts-de-France for providing us the measurements used in the study case.

Funding Information:
This work was supported by the scholarship of Excellence from the National Center for Scientific and Technical Research (CNRST) of Morocco and Université du Littoral Côte d’Opale of Dunkerque, France. We would like to thank Atmo Hauts-de-France for providing us the measurements used in the study case.

Publisher Copyright:
© 2020, Metrology Society of India.

Keywords

  • AQMs recommendations
  • Air pollution
  • Air quality models (AQMs)
  • Datasets
  • Techniques and validation

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