The Forcast of Three Major Atmospheric Pollutants Concentrations and its Relationships with Meteorological Factors in Ya'an, Sichuan Province

Yaping WU; Qi ZHANG; Bingyun WANG; Shigong WANG; Ping SHAO

doi:10.7522/j.issn.1000-0534.2019.00115

2020 , Vol. 39 >Issue 4: 889 - 898

DOI: https://doi.org/10.7522/j.issn.1000-0534.2019.00115

The Forcast of Three Major Atmospheric Pollutants Concentrations and its Relationships with Meteorological Factors in Ya'an, Sichuan Province

Yaping WU ,
Qi ZHANG ,
Bingyun WANG ,
Shigong WANG ,
Ping SHAO

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1.Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Sciences, Chengdu University of Information technology, Chengdu 610225, Sichuan, China;2.Bureau of Meteorology in Ya'an, Ya’an 625000, Sichuan, China;3.Academician work center in Zunyi, Zunyi 563000, Guizhou, China

Received date: 2019-08-20

Online published: 2020-08-28

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Abstract

Based on the need of air quality forecast and air pollution prevention in Ya'an, Sichuan, air pollution monitoring data of Ya'an City from 2015 to 2018 and meteorological data at the same period were used to analyze the correlations between the air pollutants concentrations and meteorological factors in detail by Gray Correlation Method. The short-term forecast models of air quality in Ya'an city were constructed with BP Neural Network method, and forecast results were checked too. The results showed that the pollutants concentrations of O₃, PM_2.5 and PM₁₀ in Ya'an City showed upward trends from 2015 to 2017, with the air quality passing rate dropping from 92.7% to 82.2%, but the passing rate rising slightly to 88% in 2018, however there were still 9 days with moderate pollution and 1 day with heavy pollution. The pollutants concentrations were closely related to meteorological factors, of which rainfall and air pressure were most associated with PM_2.5 and PM₁₀ pollutions, indicating that Ya'an, as the "rain city" of Sichuan, had a significant wet removal effect on particulate matter. While temperature and wind speed were most correlated with O₃ pollution, which just reflected the promotion of O₃ generation by high temperature and strong radiation implied by high temperature. Using the BP neural network, the forecast model of O₃ had a stable accuracy, with an average relative error less than 19% for each season in 7 days, and the forecast results were sorted from summer, winter, autumn to spring. The forecast models of PM_2.5 had better prediction accuracy in spring and summer, with an average relative error less than 16% in 7 days, a slightly higher relative error in autumn. This results could provide technical support for the development of local air quality forecasting operations in Ya’an.

Key words： Atmospheric pollutan; meteorological facto; gray correlation; BP neural network; forecast model

Cite this article

Yaping WU , Qi ZHANG , Bingyun WANG , Shigong WANG , Ping SHAO . The Forcast of Three Major Atmospheric Pollutants Concentrations and its Relationships with Meteorological Factors in Ya'an, Sichuan Province[J]. Plateau Meteorology, 2020 , 39(4) : 889 -898 . DOI: 10.7522/j.issn.1000-0534.2019.00115

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