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Understanding of its correlation to some relevant factors is of paramount importance for modeling and predication of the air pollution process. Compared with the traditional cross-correlation analysis, multifractal detrended cross-correlation analysis (MFDCCA) was argued to be a more suitable method to analyze air pollutant time series due to their non-stationarity nature. Multifractal temporally weighted detrended cross-correlation analysis (MF-TWXDFA) was proposed to improve the shortcomings of MFDCCA. In this study, we apply MF-TWXDFA to investigate the cross-correlation between pollutants ( PM 1 0 and NO X ) and meteorological factors (temperature, pressure, wind speed (WS) and relative humidity (RH)). The results on the dataset from 1 January 2005 to 31 December 2014 in urban and rural areas of Hong Kong show the existence of multifractal cross-correlation between all pairs of pollutants and meteorological factors in both urban and rural areas. Different from the previous MFDCCA results, we found that the multifractal degree of cross-correlation between PM 1 0 and (temperature, pressure) is more obvious in urban area. The multifractal strength of cross-correlation between NO X and WS is very weak in either urban or rural area. Furthermore, the MF-TWXDFA cross-correlation coefficient ρ MF-TWXDFA can capture negative correlation between pollutants and meteorological factors. For PM 1 0 , ρ MF-TWXDFA in urban area is less than or close to that in rural area with respect to these four meteorological factors. The ρ MF-TWXDFA of NO X in urban and rural areas shows more complex patterns for varied meteorological factors. Compared with MFDCCA, MF-TWXDFA can provide much richer information about the relationships between pollutants and meteorological factors, which is beneficial to further modeling and prediction of the air pollution process. [ABSTRACT FROM AUTHOR]