Environmental design plays an important role in urban planning and construction. Greening rate and air quality are important indicators for evaluating urban environmental quality. In order to improve the greening rate and improve air quality, the researchers used various optimization algorithms. This research is based on the Particle Swarm Optimization algorithm (PSO) and analyzes the environmental design model. It can find the best solution in the environmental design. The algorithm improves the greening rate by optimizing the greening scheme, green space layout and vegetation configuration, while reducing air pollutant emissions and improving air quality. The research results show that the greening rate of the PSO algorithm in environmental design is between 85 and 93%, and the environmental design model based on the PSO algorithm can effectively improve the greening rate and improve air quality. Through its optimization ability, the PSO algorithm has found the best greening plan and environmental layout, thereby improving the greening rate of the city.