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Overviewing the air quality models on air pollution in Sichuan Basin, China.
- Source :
-
Chemosphere . May2021, Vol. 271, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- Most developing countries in the world face the common challenges of reducing air pollution and advancing the process of sustainable development, especially in China. Air pollution research is a complex system and one of the main methods is through numerical simulation. The air quality model is an important technical method, it allows researchers to better analyze air pollutants in different regions. In addition, the SCB is a high-humidity and foggy area, and the concentration of atmospheric pollutants is always high. However, research on this region, one of the four most polluted regions in China, is still lacking. Reviewing the application of air quality models in the SCB air pollution has not been reported thoroughly. To fill these gaps, this review provides a comprehensive narration about i) The status of air pollution in SCB; ii) The application of air quality models in SCB; iii) The problems and application prospects of air quality models in the research of air pollution. This paper may provide a theoretical reference for the prevention and control of air pollution in the SCB and other heavily polluted areas in China and give some1inspirations for air pollution forecast in other countries with complex terrain. [Display omitted] • Current situation of air pollution in the Sichuan Basin of China is reviewed. • The development and classification of air quality models are summarized. • Application of air quality models in the study of Sichuan Basin air pollution are discussed. • Problems in the application and future research directions of air quality models are provided. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00456535
- Volume :
- 271
- Database :
- Academic Search Index
- Journal :
- Chemosphere
- Publication Type :
- Academic Journal
- Accession number :
- 149155355
- Full Text :
- https://doi.org/10.1016/j.chemosphere.2020.129502