Grass pollen grains cause allergic reactions in a large portion of the global popu- lation. Aerobiological monitoring provides a valuable method for assessing plant responses to climate change. Wind-pollinated plants exhibit varying responses to climate shifts, and this study aimed to analyze long-term trends in Poaceae pollen concentration in Lublin (Poland) from 2001 to 2022. Pollen seasons were analyzed using the volumetric method. The following parameters were assessed for each season: onset, end, duration, peak value, date of peak, number of high-pollen days, and annual pollen sum. Meteorological data were collected for the same period. Statistical analysis was performed using Spearman’s rank correlation to examine relationships between pollen season parameters and meteorological factors, and multivariate regression models were developed to explore the influence of specific climate variables on pollen season dynamics. Additionally, principal component analysis (PCA) was applied for visual comparisons of grass seasons. The analysis revealed a significant decline in the annual pollen sum, the July pollen sum, and the number of high pollen days, with the most substantial changes occurring in July. The decrease in the annual pollen sum was significantly associated with lower humidity in March and May and higher temperatures in June. Peak pollen values were negatively correlated with increased sunshine in March and April and positively correlated with humidity in March and May, while humidity levels strongly influenced the number of high-pollen days. The intensity of the grass pollen season notably weakened after 2011, in alignment with broader trends observed across Europe, attributed to climate change. These findings highlight the substantial influence of climatic variables on the grass pollen season, with implications for individuals with respiratory allergies. The results also underscore the broader public health and ecological impacts of climate change, suggesting the need for continued monitoring and adaptive measures.