This study investigates the annual cycle of particulate matter (PM) concentrations in Krakow, Poland, using a dense grid of low-cost sensors. The research reveals two main PM seasons—warm and cold—distinct from traditional seasonal divisions. These seasons are influenced by temperature, with cold periods linked to coal burning for heating and warm periods associated with agricultural burning. The study highlights the importance of high-resolution data for urban planning and shows that air pollution in Krakow is significantly affected by geographical factors, including topography and wind patterns. Air pollution has severe health and environmental impacts, including respiratory and cardiovascular diseases, and contributes to climate change. The study also demonstrates the effectiveness of big data analytics in understanding the relationship between climate and air pollution, identifying key meteorological factors such as temperature, humidity, and pressure. The findings emphasize the need for targeted measures to reduce air pollution, particularly in urban areas. The research uses data from low-cost sensors and public datasets to analyze PM concentrations and their spatial and temporal variations, revealing high-emission episodes in certain regions, such as the northeastern area, possibly linked to illegal burning of agricultural land. The study also shows that air quality in Krakow varies significantly throughout the year, with the worst air quality in March and December 2021. The results provide valuable insights into the dynamics of air pollution in urban areas and highlight the need for further research and implementation of appropriate measures to reduce air pollution. The study underscores the importance of integrating meteorological data with air pollution monitoring to develop effective strategies for improving air quality in urban environments.This study investigates the annual cycle of particulate matter (PM) concentrations in Krakow, Poland, using a dense grid of low-cost sensors. The research reveals two main PM seasons—warm and cold—distinct from traditional seasonal divisions. These seasons are influenced by temperature, with cold periods linked to coal burning for heating and warm periods associated with agricultural burning. The study highlights the importance of high-resolution data for urban planning and shows that air pollution in Krakow is significantly affected by geographical factors, including topography and wind patterns. Air pollution has severe health and environmental impacts, including respiratory and cardiovascular diseases, and contributes to climate change. The study also demonstrates the effectiveness of big data analytics in understanding the relationship between climate and air pollution, identifying key meteorological factors such as temperature, humidity, and pressure. The findings emphasize the need for targeted measures to reduce air pollution, particularly in urban areas. The research uses data from low-cost sensors and public datasets to analyze PM concentrations and their spatial and temporal variations, revealing high-emission episodes in certain regions, such as the northeastern area, possibly linked to illegal burning of agricultural land. The study also shows that air quality in Krakow varies significantly throughout the year, with the worst air quality in March and December 2021. The results provide valuable insights into the dynamics of air pollution in urban areas and highlight the need for further research and implementation of appropriate measures to reduce air pollution. The study underscores the importance of integrating meteorological data with air pollution monitoring to develop effective strategies for improving air quality in urban environments.