Abstract: The study chose Jiangxi Province as the study area, to explore the spatio-temporal characteristics of urbanization development and atmospheric particulate matter pollution and their coupling coordination relationship. It is expected to provide effective reference on coordination between urbanization and the atmospheric environment for Jiangxi Province and other less developed areas. Spatial autocorrelation method was used to analyze the spatio-temporal distribution characteristics of urbanization level and atmospheric particulate matter, and coupling coordination degree model was constructed to analyze spatio-temporal variation of relationship between urbanization level and atmospheric particulate matter. The results show that：(1) From 2015 to 2019, the comprehensive urbanization level increased steadily, and concentrations of PM_2.5 and PM₁₀ increased first and then decreased. (2) The comprehensive urbanization level present spatial discrete characteristic, PM_2.5 and PM₁₀ concentrations present obvious spatial agglomeration characteristic since 2016. The local autocorrelation characteristics of comprehensive urbanization level, PM_2.5 and PM₁₀ are highly consistent, showing spatial overall distribution characteristic of "high in the northwest and low in the southeast". (3) From 2015 to 2019, the coupling coordination degree between comprehensive urbanization level and atmospheric environment increased，showing the urbanization development is atmosphere-friendly. Increase of coupling coordination degree between 11 cities are significantly different, and there is still large improvement for some cities. The coupling coordination degree is spatially discrete, with a distribution pattern of "high in the middle and low around". Nanchang, the capital of Jiangxi, has already achieved a good coordination between urbanization and atmospheric environment. However, most of the other cities are still developing at the cost of decreasing ecological environment. It is suggested to explore new urbanization paths for different cities according to the regional characteristics.