| Ambient air quality is the current hot topic of social concern, the relevant departments announced the ambient air quality data in real time, including air quality monitoring Air Quality Index (AQI) and PM2.5, PM10, SO2, CO, NO2, O3 concentration six indicators data. First, the use of the data, the air quality index for information and six changes of monitoring indicators and the main influencing factors derived from the concentration values in the abstract, Intuitively and quickly established by the X (pollutant concentrations) to Y (AQI) mappings, the concentration value by making abstract mathematical model into the air quality index can integrate with a variety of environmental evaluation methods, laws and regulations, to facilitate the environmental assessment and environmental management.In this paper, the trend to reflect the relationship between intuitive and effective annual air quality index and six monitoring indicators, radiation from the wind speed, rainfall, sun, geography and other meteorological factors and pollutant emissions do cause analysis. Thereafter, in order to find out the impact of air pollution indicators affecting mainly the environment, we use principal component analysis of the collected data processing analysis, the main environmental effects of air pollutants as particulate matter and nitrogen dioxide, combined with real life analysis of the main pollutants and dust pollution comes mainly from vehicle exhaust emissions. Finally, a linear regression model to Kunming in 2014 to predict the air quality index, after culling through several outliers. And using the correlation coefficient R2, F test, P test, and compare the observed and predicted values map to verify that there is a high linear regression model with real data obtained by similarity. Using this model we can in the coming years Kunming air quality forecast, but also facilitate the future more targeted for ambient air quality management. |
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