A field study was conducted in small-scale urban green spaces in Zhengzhou to monitor PM2.5 and PM10 concentrations along with temperature, humidity, and wind speed. Data analysis using SPSS revealed that PM2.5 showed a fluctuating decline throughout the day, while PM10 steadily decreased. No significant spatial differences were found in PM2.5, PM10, temperature, or humidity between the interiors and exteriors of the green spaces, but wind speed varied significantly. The reduction in PM2.5 and PM10 concentrations was influenced by distance from pollution sources and canopy density, with greater distances and sparser canopies leading to lower concentrations. However, the reduction rates remained below 5%, indicating a weak effect. Meteorological factors played a key role: PM2.5 was negatively correlated with temperature and positively with humidity, while its correlation with wind speed was not significant. PM10 was positively associated with humidity and negatively with both temperature and wind speed. A regression model estimated that a 1°C increase in temperature could decrease PM2.5 by 0.502 μg/m3 and PM10 by 3.586 μg/m3. Based on these findings, an optimized strategy for small-scale green space design is proposed to improve air quality while meeting urban functional needs.