Scientific deployment and comprehensive monitoring: Based on the development of industries such as economy, population, transportation, and industry, intelligently and scientifically plan the construction of new air quality monitoring stations. The deployment plan saves project investment, avoids excessive resource waste, and enables scientific and accurate data collection;

Data interconnection and sharing: The system can simultaneously forward raw data to district, city, provincial, and national environmental protection departments, as well as multi-level and multiple environmental monitoring centers. It provides standard interfaces with other government departments, city, provincial, and national environmental quality monitoring systems, environmental quality networking systems, and other monitoring systems to achieve data exchange and interconnection sharing between different monitoring systems.

Pollution source analysis and tracing: Using big data technology and a professional air quality modeling system, dynamically analyze the formation, transmission, and diffusion of pollution, quantitatively analyze the causes and changes of pollution, and trace the pollution sources;

Warning and forecasting: In the event of equipment abnormalities or current monitoring exceeding the standard, automatic alarm information will be sent to relevant contacts, providing accurate and reliable information on the exceeding value, exceeding time, exceeding emission amount, and exceeding emission medium quality, providing a detailed and reliable basis for strengthening supervision work. By using the most authoritative numerical and statistical forecasting models, scientific and reasonable analysis and prediction of the future will be carried out according to the laws and trends of air quality changes10Assess the impact of environmental air pollution on the atmosphere caused by changes in air quality in the sky;

Pollution assessment and quality daily report: According to data validity regulationsAQIEvaluate technical specifications, data inversion and revision regulations, conduct data review and processing, evaluate the air quality data of each sub station, use monitoring results to release daily reports, forecasts, and regular quality reports on environmental air quality to the public, and strengthen the public's supervisory role.

Decision support: Using big data technology to scientifically determine the contribution rates of annual, seasonal, and monthly pollutants from different types of pollution sources to the degree of pollution; Quantitatively analyze and evaluate the implementation effects of emission reduction and control policies and measures adopted in different regions, time periods, and meteorological conditions, and guide industries and enterprises to achieve the optimal pollution control effect with the minimum emission reduction cost based on the evaluation results and established emission reduction targets, in order to improve the sustainability of emission reduction and control measures.

By adopting grid based data transmission, fixed-point monitoring, and global analysis, we can achieve statistical and comparative analysis of environmental air quality in different regions, functional points, and time periods. We can discover the changing patterns of pollution sources, locate the most severely polluted areas and time periods, and provide timely and effective guarantees for environmental law enforcement and decision-making.