Spatio-temporal trajectory evolution and cause analysis of air pollution in Chengdu, China

Figures & data

Figure 1. Location of the Chengdu in China and three-dimensional terrain in the Chengdu and its surrounding areas.

Figure 2. Variation Characteristics of daily average AQI concentration, distribution of pollution days and proportion of AQI grade in Chengdu from 2015 to 2018.

Table 1. Random forest classification of air pollutants in Chengdu 2017.

Cluster		PM2.5(μg·m^−3)	PM10(μg·m^−3)	SO2(μg·m^−3)	NO2(μg·m^−3)	CO(μg·m^−3)	O3(μg·m^−3)
1	average	129.24 ± 29.08	185.34 ± 39.05	16.11 ± 4.29	75.39 ± 13.00	1.56 ± 0.25	50.37 ± 31.15
	days	38	38	38	38	38	38
2	average	65.41 ± 20.65	102.45 ± 28.85	13.00 ± 3.65	60.48 ± 9.52	1.07 ± 0.17	57.67 ± 37.41
	days	92	92	92	92	92	92
3	average	26.72 ± 12.69	45.96 ± 18.45	8.96 ± 1.55	40.02 ± 8.75	0.78 ± 0.15	79.49 ± 34.05
	days	135	135	135	135	135	135
4	average	36.08 ± 16.17	63.38 ± 25.26	10.09 ± 2.87	48.58 ± 12.59	0.83 ± 0.13	172.66 ± 31.79
	days	89	89	89	89	89	89
5	average	214.45 ± 41.86	320.55 ± 67.29	18.55 ± 4.66	93.55 ± 19.23	2.19 ± 0.30	39.27 ± 24.92
	days	11	11	11	11	11	11

Table 2. Basic concentration limit of ambient air pollutants.

		Concentration Limit (μg·m-3)
Pollutant	Mean time	level I	level II
SO2	24 hour	50	150
NO2	24 hour	80	80
CO	24 hour	4	4
O3	8 hour	100	160
PM10	24 hour	50	150
PM2.5	24 hour	35	75

Figure 3. Classification frequency chart of air pollutants in Chengdu 2017.

Figure 4. The air spatio-temporal trajectories of each pollution period in Chengdu 2017.

Figure 5. The pollutants (PM_2.5, PM₁₀ and NO₂) of occurrence probability and corresponding concentration of each air trajectory during serious pollution period in Chengdu 2017.

Figure 6. The O₃ of occurrence probability and corresponding concentration of each air trajectory during O₃ pollution period in Chengdu 2017.

Figure 7. The pollutants (PM_2.5, PM₁₀) of occurrence probability and corresponding concentration of each air trajectory during slight pollution period in Chengdu 2017.

Figure 8. Spatial distribution of WPSCF and WCWT values of PM_2.5, PM₁₀ and NO₂ of serious pollution period in Chengdu 2017.

Figure 9. Spatial distribution of WPSCF and WCWT values of O₃ of Ozone pollution period in Chengdu 2017.

Figure 10. Spatial distribution of WPSCF and WCWT values of PM_2.5 and PM₁₀ of light pollution period in Chengdu 2017.

Figure 11. The hourly, daily and monthly variations of PM_2.5, PM₁₀, NO₂ and O₃ in Chengdu in 2017.

Figure 12. The hourly variation of meteorological data (temperature, relative humidity, and wind speed), AOD, PBLH and pollutant gases (PM_2.5, PM₁₀, NO₂ and O₃) in Chengdu 2017.

Figure 13. Distribution of thermal anomalies in typical industrial areas: a is a cement plant; b is a steel plant; c is a manufacturing plant.

Figure 14. Hourly distribution relationship between wind speed and pollution in each pollution period.

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request. http://sweb.cdutetc.cn/tmgc/wxj/20220407.rar