  In recent years, China has made great efforts to control air pollution.
During the governance process, it is found that fine particulate matter (PM2.5)
and ozone (O3) change in the same trend among some areas and the opposite in
others, which brings some difficulties to take measures in a planned way.
Therefore, this study adopted multi-year and large-scale air quality data to
explore the distribution of correlation between PM2.5 and O3, and proposed a
concept called dynamic similar hu lines to replace the single fixed division in
the previous research. Furthermore, this study discussed the causes of
distribution patterns quantitatively with geographical detector and random
forest. The causes included natural factors and anthropogenic factors. And
these factors could be divided into three parts according to the
characteristics of spatial distribution: broadly changing with longitude,
changing with latitude, and having local characteristics. Overall, regions with
relatively more densely population, higher GDP, lower altitude, higher
humidity, higher atmospheric pressure, higher surface temperature, less
sunshine hours and more accumulated precipitation often corresponds to positive
correlation coefficient between PM2.5 and O3, no matter in which season. The
parts with opposite conditions that mentioned above are essentially negative
correlation coefficient. And what's more, humidity, global surface temperature,
air temperature and accumulated precipitation are four decisive factors to form
the distribution of correlation between PM2.5 and O3. In general, collaborative
governance of atmospheric pollutants should consider particular time and space
background and also be based on the local actual socio-economic situations,
geography and geomorphology, climate and meteorology and other comprehensive
factors.
