Correlation Analysis Between Air Pollution And Meteorological Conditions In Chengdu And Design Of Forecast And Early Warning System

Over the past few years,regional air environmental problems of China have become increasingly prominent,and the air pollution situation has been severe,which has caused a series of adverse effects on agricultural production.In order to effectively improve air quality,the Chinese government has formulated a series of effective regulatory policies.In 2013,the "Air Pollution Prevention and Control Plan" was issued,and the "Three-Year Action Plan for Winning the Blue Sky Defense" was issued in 2018,etc.,which effectively achieved air quality.The air pollution prevention and control system and mechanism have been initially established,but the current air pollution situation in China is still severe.As a new first-tier city,Chengdu is located in the hinterland of the Chengdu Plain.It has a suitable climate and a well-developed agricultural industry.In order to understand the future air pollution situation in advance,relevant countermeasures should be formulated as soon as possible to reduce pollution in advance,so as to further optimize the agricultural production environment and establish an air pollution monitoring and forecasting system is very necessary.The research content of this paper is as follows:(1)Analyze the temporal and spatial distribution characteristics of meteorological data and pollutant data in Chengdu from 2017 to 2018.It is found that the air quality in Chengdu has shown an overall improvement trend in recent years,and the regularity of atmospheric pollutants with seasonal changes is extremely strong;(2)Carry out correlation analysis of atmospheric pollutants and meteorological conditions.Because the air quality index is affected by multiple meteorological factors,it is complicated to measure.In order to accurately predict;(3)Construct an improved LSTM prediction model based on AMPSO,and compare the BP prediction model with the LSTM prediction model,and it is found that the AMPSO-LSTM prediction model is significantly better than the BP prediction model and LSTM prediction model;(4)Develop an air pollution monitoring and forecasting system based on the AMPSO-LSTM neural network to present data and forecast the pollutant concentration.The results show that the system can achieve the functional requirements of the system and meet the requirements of users,having good availability and reliability.