In this section, we examine the regional patterns of different meteorological variables. These patterns set up the local conditions for the occurrence of air pollution. A few studies have examined the flow patterns and their impacts on the occurrence of pollution in Beijing (Ye et al., 2016; Zhang et al., 2015). Here, we contrast the regional patterns of four meteorological variables (air temperature, sea level pressure, relative humidity, and wind speed) corresponding to polluted and clean days in Beijing.
The polluted and clean days are defined as the top and bottom 10% of the PM10 values in Beijing, respectively. There are 63 days for each category in individual seasons. Table 1 shows the mean PM10 values for the polluted and clean days in the four seasons. The standard deviations of PM10 values in each category are also included to provide information about the differences among the selected cases. For the polluted days, the highest mean PM10 value (307.9 μg m–3) is in spring and the lowest mean PM10 value (188.5 μg m–3) is in summer. Note that the selected cases have mean PM10 values well above the national standard of 150 μg m–3 (He et al., 2014) for polluted days by more than one standard deviation in all the four seasons. Thus, the majority of the selected cases correspond to heavy pollution events. For the clean days, the lowest PM10 value (26.0 μg m–3) is in winter and the highest mean PM10 value (40.3 μg m–3) is in spring. Composite maps for the polluted and clean days are constructed for the 4 reanalysis variables in different seasons by averaging reconstructed variations with periods shorter than 90 days (called anomalies, to distinguish them from original values) at each grid point. In the following, we examine surface air temperature, sea level pressure, lower-level relative humidity, and surface wind anomalies, separately.
Polluted days Clean days Spring 307.93 (103.61) 40.30 (17.48) Summer 188.45 (36.18) 35.85 (18.21) Fall 268.36 (57.88) 27.85 (12.65) Winter 294.99 (90.15) 26.04 (12.53)
Table 1. The mean and standard deviation (in parenthesis) of PM10 concentration (μg m–3) during polluted and clean days in the four seasons. The polluted and clean days refer to the top and bottom 10% of the PM10 values
The surface air temperature anomaly shows a pronounced difference between polluted and clean days. On polluted days, air temperature is higher in most of eastern China (Fig. 3, left-hand panels). Positive temperature anomalies appear in northern China in all four seasons as well, as in southern China in spring, fall, and winter. In comparison, the temperature anomalies are smaller in summer compared to the other three seasons. Opposite temperature anomalies with similar features are observed on clean days (Fig. 3, right-hand panels). The differences in temperature anomalies between polluted and clean days are significant over most regions of eastern China. Locally, polluted days correspond to higher air temperature and clean days correspond to lower temperature. This is consistent with the correlation highlighted in the previous section between PM concentration and air temperature. This consistency indicates that local temperature change occurs under a regional pattern of temperature anomalies.
Figure 3. Composite anomalies of 2-m air temperature Ta (K) on (a, c, e, g) polluted and (b, d, f, h) clean days in (a, b) spring, (c, d) summer, (e, f) fall, and (g, h) winter, based on PM10 concentration. Dotted regions denote that the difference between the polluted and clean days is significant at the 95% confidence level. The location of Beijing is indicated in Fig. 1a.
The sea level pressure and surface wind anomalies also display a prominent contrast between polluted and clean days. On polluted days, lower sea level pressure covers eastern China in spring, fall, and winter (Figs. 4a, e, g). Consistently, southerly or southeasterly wind anomalies blow from the tropical western North Pacific to Northeast China and southerly wind anomalies cover southern China (Figs. 4a, e, g). The wind anomalies are weak over northern China. This indicates lower-level anomalous wind convergence around Beijing, which is favorable for accumulation of aerosol particles. In summer, the sea level pressure anomaly displays a distribution featuring higher pressure to the southeast and lower pressure to the northwest of Beijing (Fig. 4c), consistent with Zhao et al. (2016a). Anomalous southerly winds cover northern China (Fig. 4c). Such southerly winds may bring more air from regions south of Beijing where more emissions are located (Wang et al., 2010; Tian et al., 2014).
Figure 4. As in Fig. 3, but for sea level pressure (SLP; hPa) and wind at 10 m (m s–1). Only wind vectors with zonal and/or meridional wind difference significant at the 95% confidence level are plotted.
On clean days, opposite pressure and wind anomalies are observed, with similar distributions (Fig. 4, right-hand panels). The pressure anomaly difference between polluted and clean days is significant over many regions. During spring, fall, and winter, northerly/northwesterly wind anomalies increase from northern China to the subtropical western North Pacific (Figs. 4b, f, h), indicating lower-level anomalous wind divergence around Beijing, favorable for dispersion of aerosol particles. During summer, anomalous northerly winds (Fig. 4d) may reduce the transport of aerosol particles from the south.
The contrast in local surface pressure and wind anomalies between polluted and clean days is consistent with the correlation analysis. For example, in summer, the small local pressure difference between polluted and clean days around Beijing agrees with the weak correlation between PM concentration and surface pressure. In spring, fall, and winter, southerly (northerly) wind anomalies on polluted (clean) days around Beijing indicate a weakening of surface winds, as climatological mean winds are northerly, which agrees with the local negative correlation of surface wind speed. The consistency suggests that local meteorological conditions for air pollution changes are controlled by the regional meteorological pattern.
Relative humidity displays opposite anomalies in fall and winter between polluted and clean days. Relative humidity in northern China is higher on polluted days (Figs. 5e, g), but lower on clean days (Figs. 5f, h). In spring and summer, the relative humidity anomalies around Beijing are negative on polluted days (Figs. 5a, c), but positive on clean days (Figs. 5b, d). The anomalies in spring and summer are opposite to those in fall and winter, indicative of a strong seasonal dependence of the relative humidity anomalies. The results are mostly consistent with the correlation analysis in fall and winter, but not so in spring and summer. Previous studies have indicated that air pollution tends to occur on high relative humidity days (Tian et al., 2014; Zhang et al., 2015; Ye et al., 2016). Our results indicate that this may not be applicable to high frequency day-to-day variations in spring and summer.
Figure 5. As in Fig. 3, but for relative humidity (%) at 1000 hPa.
|Polluted days||Clean days|
|Spring||307.93 (103.61)||40.30 (17.48)|
|Summer||188.45 (36.18)||35.85 (18.21)|
|Fall||268.36 (57.88)||27.85 (12.65)|
|Winter||294.99 (90.15)||26.04 (12.53)|