Research on Precise Monitoring and Prevention of Environmental Pollution Based on Environmental Big Data Analysis
Abstract
Environmental big data analysis has become an important approach for achieving intelligent environmental governance, while reliable wireless communication and electromagnetic signal transmission provide the essential infrastructure for distributed sensing and real-time data acquisition in modern monitoring systems. This study established a VOC-based online monitoring cloud platform to analyze gas distribution characteristics within a chemical park. Five monitoring stations were deployed to continuously collect real-time VOC concentration data, enabling the evaluation of localized pollution patterns and emission characteristics. Based on the acquired VOC datasets, environmental information was uploaded to the cloud platform through wireless communication networks and analyzed using the USEPA Positive Matrix Factorization (PMF) model to identify and localize pollution sources with high precision. The results demonstrate that the proposed framework effectively distinguishes multiple VOC emission sources, including alkane leakage, preparation process emissions, olefin synthesis, urban transmission, and storage tank emissions, thereby providing accurate source apportionment and spatial localization for environmental management. By integrating environmental big data analytics with cloud-based monitoring architecture and electromagnetic information transmission technologies, the proposed approach enhances the efficiency and reliability of real-time pollution surveillance and offers a practical reference for intelligent environmental monitoring and industrial emission prevention.