Research on Air Quality in Response to Meteorological Factors Based on the Informer Model

Xiaoqing Tian, Chaoqun Zhang, Huan Liu, Baofeng Zhang, Cheng Lu, Pengfei Jiao and Songkai Ren ()
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Xiaoqing Tian: International Co-Operation Platform of Intelligent Ocean Equipments Technology of Zhejiang Province, Hangzhou Dianzi University, Hangzhou 310052, China
Chaoqun Zhang: International Co-Operation Platform of Intelligent Ocean Equipments Technology of Zhejiang Province, Hangzhou Dianzi University, Hangzhou 310052, China
Huan Liu: School of Cyberspace Security, Hangzhou Dianzi University, Hangzhou 310018, China
Baofeng Zhang: Hangzhou Eco-Environment Monitoring Center, Hangzhou 310012, China
Cheng Lu: Zhejiang Institute of Hydraulics & Estuary, Hangzhou 310020, China
Pengfei Jiao: School of Cyberspace Security, Hangzhou Dianzi University, Hangzhou 310018, China
Songkai Ren: International Co-Operation Platform of Intelligent Ocean Equipments Technology of Zhejiang Province, Hangzhou Dianzi University, Hangzhou 310052, China

Sustainability, 2024, vol. 16, issue 16, 1-22

Abstract: The quality of the air exerts considerable effects on human health, and meteorological factors affect air quality. The relationships between meteorological factors and air quality parameters are complex dependency correlations. This article is based on the air quality monitoring data and meteorological monitoring data obtained from a monitoring station in Binjiang District, Hangzhou City, China, spanning from 01:00 on 14 April 2021 to 23:00 on 31 December 2021. The Informer model was used to explore the air quality parameters’ response to meteorological factors. By analyzing 12 different kinds of 2-Minute Average Wind Speed (2-MAWSP), 10-Minute Average Wind Speed (10-MAWSP), and Maximum Wind Speed (MXSPD); 16 different kinds of Hourly Precipitation (HP) and Air Temperature (AT); 11 different kinds of Relative Humidity (RH); and 8 different kinds of Station Pressure (STP), the following results were obtained: (1) The influence of wind speed on various air quality parameters is multifaceted and lacks a standardized form, potentially influenced by factors like wind direction and geographical location. One clear effect of wind speed is evident in the levels of particulate matter 10 (with an aerodynamic diameter smaller than 10 μm, PM 10 ), as the values of this parameter first decrease and then increase with increasing wind speed. (2) HP has an evident reducing effect on most air quality parameters, including particulate matter (including PM 2.5 and PM 10 ), ozone (O 3 ), sulfur dioxide (SO 2 ), and nitrogen dioxide (NO 2 ), as well as nitrogen oxides (NO x ). (3) The increase in AT has a clear reducing effect on the concentration of NO 2 , while the trend for the concentrations of PM 10 and NO x is one of initial decrease followed by a gradual rise. (4) RH only reduces the concentrations of SO 2 and PM 10 . (5) With the rise in STP, the concentrations of most air quality parameters generally rise as well, except for the decrease in NO x concentration. This can give some indications and assistance to meteorological and environmental departments for improving air quality. This model can be used for a performance analysis and the forecasting of multi-parameter non-correlated systems.

Keywords: air quality parameters; meteorological factors; response; informer model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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