Study on the Spatial and Temporal Distribution Characteristics and Influencing Factors of Particulate Matter Pollution in Coal Production Cities in China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Research Area and Data Sources
2.2. Analysis of Socioeconomic Factors
2.3. Trajectory Analysis
2.3.1. Cluster Analysis
2.3.2. Potential Source Contribution Function (PSCF)
3. Results and Discussion
3.1. Spatial–Temporal Distribution Characteristics of Particulate Matter Concentration
3.2. Influence of Social-Economic Factors on Particulate Matter
3.3. Influence of Natural Factors on Particulate Matter
4. Conclusions
- (1)
- During 2015 to 2019, the average annual concentration of PM2.5 and PM10 increased first and then decreased, reaching the peak in 2017. Temporally, PM2.5 and PM10 presented a “U” shaped change pattern for monthly variation, and a double-peak and double-valley pattern for diurnal variation. Spatially, PM2.5 and PM10 concentration of TY and YQ in the central region and LF and JC in the southern region is higher, and EEDS and YL in the western region are relatively light.
- (2)
- In terms of social-economic factors, PM2.5 has a significant correlation with SI, PD, GC and CO. Differently, PM10 has a significant correlation with GC and CO, and a poor correlation with other social-economic factors. Specifically, PM2.5 has an “inverted U-shaped” quadratic polynomial relationship with SI and PD, and a U-shaped relationship with GC and CO.
- (3)
- In terms of natural factors, PM2.5 and PM10 are significantly positively correlated with NO2, SO2, CO and Pressure, and significantly negatively correlated with O3 and Temperature. Notably, wind speed has a significant negative correlation with PM2.5 and a significant positive correlation with PM10. Moreover, backward trajectory cluster analysis shows that the air mass trajectory in TY is mainly from the northwest direction, followed by the southwest direction and the east direction. In the northwest, there are many trajectories of long-distance transmission each year. PSCF analysis results show that the southwest region of TY is a high potential source of fine particulate matter pollution, and the long-distance transport of PM2.5 from Xinjiang in the northwest also contributes to fine particulate matter pollution to a certain extent. This paper discusses the influence of natural factors and social and economic factors on the concentration of particulate matter in coal production cities. In the follow-up work, the influence of various industries on particulate matter pollution can also be detailed, which will help decision-makers to consider these related air pollution conditions when formulating future urban development policies.
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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PM2.5 | PM10 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Year | Parameter | SI | GDP | PD | GC | OC | SI | GDP | PD | GC | OC |
2015 | R2 | 0.64 * | 0.24 | 0.52 * | 0.72 ** | 0.73 ** | 0.37 | 0.10122 | 0.73 ** | 0.45 | 0.53 * |
b1 | 0.05570 | 0.00077 | 0.14981 | 0.04629 | −0.00079 | 0.05915 | −0.01826 | 0.19445 | 0.03317 | −0.00076 | |
b2 | −0.00004 | 0.00000 | −0.00017 | −0.00011 | 0.00000 | −0.00004 | 0.00000 | −0.00020 | −0.00009 | 0.00000 | |
Constant | 37.31681 | 55.43423 | 29.56998 | 50.60329 | 61.89346 | 79.40285 | 111.18117 | 65.78631 | 96.47074 | 105.85320 | |
2016 | R2 | 0.66 ** | 0.24 | 0.57 * | 0.66 ** | 0.63 * | 0.52 * | 0.20 | 0.65 ** | 0.66 ** | 0.70 ** |
b1 | 0.08242 | 0.01819 | 0.22010 | −0.00564 | −0.00102 | 0.07577 | −0.02957 | 0.29224 | −0.10892 | −0.00203 | |
b2 | −0.00005 | −0.00001 | −0.00025 | −0.00006 | 0.00000 | −0.00005 | 0.00001 | −0.00032 | 0.00003 | 0.00000 | |
Constant | 30.40025 | 46.04485 | 21.45023 | 63.14374 | 65.60328 | 83.15594 | 129.85351 | 58.40048 | 131.28330 | 122.99882 | |
2017 | R2 | 0.53 * | 0.24 | 0.48 | 0.72 ** | 0.72 ** | 0.50 * | 0.17 | 0.44 | 0.76 ** | 0.71 ** |
b1 | 0.04309 | 0.00037 | 0.21455 | −0.06208 | −0.00156 | 0.06639 | −0.02285 | 0.22438 | −0.14540 | −0.00244 | |
b2 | −0.00003 | 0.00000 | −0.00025 | 0.00000 | 0.00000 | −0.00004 | 0.00000 | −0.00022 | 0.00007 | 0.00000 | |
Constant | 45.00104 | 62.09259 | 24.99976 | 76.73892 | 73.23390 | 89.05378 | 133.89126 | 73.89322 | 147.32929 | 133.74660 | |
2018 | R2 | 0.41 ** | 0.20 | 0.56 * | 0.79 ** | 0.71 ** | 0.30 | 0.09 | 0.48 | 0.55 * | 0.55 * |
b1 | 0.01957 | −0.01212 | 0.17716 | −0.07201 | −0.00126 | 0.02991 | −0.02713 | 0.11934 | −0.06933 | −0.00163 | |
b2 | −0.00001 | 0.00000 | −0.00020 | 0.00003 | 0.00000 | −0.00001 | 0.00001 | −0.00008 | 0.00002 | 0.00000 | |
Constant | 46.30296 | 65.98086 | 24.57951 | 72.64170 | 64.69729 | 99.06534 | 135.54831 | 87.24706 | 130.11946 | 125.60507 | |
2019 | R2 | 0.25 | 0.10 | 0.57 * | 0.64 * | 0.60 * | 0.36 | 0.18 | 0.32 | 0.55 * | 0.54 * |
b1 | 0.00934 | −0.00741 | 0.14579 | −0.08980 | −0.00090 | 0.01014 | −0.01464 | 0.14274 | 0.02075 | −0.00069 | |
b2 | −0.00001 | 0.00000 | −0.00015 | 0.00005 | 0.00000 | −0.00001 | 0.00000 | −0.00014 | −0.00004 | 0.00000 | |
Constant | 43.18883 | 53.97019 | 22.01969 | 70.07539 | 55.57668 | 92.72066 | 110.43906 | 69.47818 | 94.19326 | 102.71590 |
PM2.5 | PM10 | SO2 | NO2 | O3 | CO | T | P | WS | |
---|---|---|---|---|---|---|---|---|---|
PM2.5 | 1 | ||||||||
PM10 | 0.869 ** | 1 | |||||||
SO2 | 0.713 ** | 0.644 ** | 1 | ||||||
NO2 | 0.599 ** | 0.584 ** | 0.559 ** | 1 | |||||
O3 | −0.307 ** | −0.317 ** | −0.319 ** | −0.679 ** | 1 | ||||
CO | 0.873 ** | 0.713 ** | 0.789 ** | 0.656 ** | −0.355 ** | 1 | |||
T | −0.352 ** | −0.333 ** | −0.445 ** | −0.258 ** | 0.408 ** | −0.344 ** | 1 | ||
P | 0.275 ** | 0.261 ** | 0.365 ** | 0.266 ** | −0.544 ** | 0.306 ** | −0.862 ** | 1 | |
WS | −0.079 ** | 0.042 * | −0.093 ** | −0.123 ** | 0.040 * | −0.132 ** | 0.137 ** | −0.074 ** | 1 |
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Wang, J.; Li, T.; Li, Z.; Fang, C. Study on the Spatial and Temporal Distribution Characteristics and Influencing Factors of Particulate Matter Pollution in Coal Production Cities in China. Int. J. Environ. Res. Public Health 2022, 19, 3228. https://doi.org/10.3390/ijerph19063228
Wang J, Li T, Li Z, Fang C. Study on the Spatial and Temporal Distribution Characteristics and Influencing Factors of Particulate Matter Pollution in Coal Production Cities in China. International Journal of Environmental Research and Public Health. 2022; 19(6):3228. https://doi.org/10.3390/ijerph19063228
Chicago/Turabian StyleWang, Ju, Tongnan Li, Zhuoqiong Li, and Chunsheng Fang. 2022. "Study on the Spatial and Temporal Distribution Characteristics and Influencing Factors of Particulate Matter Pollution in Coal Production Cities in China" International Journal of Environmental Research and Public Health 19, no. 6: 3228. https://doi.org/10.3390/ijerph19063228