RETRACTED ARTICLE: Analysis of PM2.5 air pollution sources based on image recognition and tracking of sports training process

Abstract

With the rapid development of social economy and the acceleration of urbanization, air quality is also facing many challenges. Recently, through effective control of pollutant emissions, the number of foggy days and PM2.5 concentration in city T tends to decrease, and air quality has been greatly improved, but haze pollution still occurs occasionally in this area. Analyzing the sources of PM2.5 by industry is particularly important for further improving the air environment quality in T city and implementing targeted industry control. To this end, this study simulated the PM2.5 pollution characteristics of city T in January, April, July, and October 2019 based on the Models-3/CMAQ 3D air quality model and compared and verified the PM2.5 concentration. In practical applications, we will analyze and study the sources of PM2.5 pollution in T cities in the industry based on the “return to zero method” of source analysis based on image recognition and within the framework of a unified model. It is especially important to correctly understand the impact of the target direction on the academic performance of sports training students. The sports field goal setting vector table deeply understands the achievement goal orientation and academic performance of sports training students through literature data methods, questionnaire survey methods, and mathematical statistics methods and provides empirical evidence for teachers to track education. Reference materials are provided by professional students, who manage and develop sports training in a more targeted way in the sports academy. Through the research of image recognition, this paper applies it to the research of PM2.5 air pollution sources and the tracking of sports training process, thereby promoting the better development of air quality and sports training.