Spatio-Temporal Variation Characteristics of PM2.5 in the Beijing–Tianjin–Hebei Region, China, from 2013 to 2018
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Control
2.3. Spatial Autocorrelation
2.4. K-Mean Clustering Algorithm
2.5. Geographic Detector
3. Results
3.1. Temporal Variations
3.1.1. Overview of Particulate Matter (PM2.5) Pollution
3.1.2. PM2.5 Mass Concentration in Regions and Cities
3.2. Spatial Variations
3.2.1. PM2.5 Spatial Evolution
3.2.2. Spatial Autocorrelation Analysis
3.3. Driving Forces of PM2.5 Pollution
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Statistic | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 |
---|---|---|---|---|---|---|
PM2.5 mass concentration (μg/m3) | ||||||
Annual Average | 98.9 | 94.8 | 77.1 | 69.9 | 64.9 | 55.6 |
Minimum | 8.8 | 13.5 | 10.1 | 10.5 | 10.5 | 8.9 |
Median | 81.6 | 78.7 | 62.1 | 58.2 | 52.9 | 44.7 |
Maximum | 326.3 | 290.1 | 313.3 | 305.4 | 260.3 | 244.9 |
Std. Dev. | 57.5 | 54.9 | 54.6 | 51.8 | 44.4 | 36 |
NOSC 1 | 0 | 0 | 1 | 1 | 2 | 2 |
NOMS 2 | 88 | 102 | 102 | 99 | 96 | 92 |
Percentage of air quality of different grades (%) | ||||||
Excellent (0–50) 3 | 13 | 14 | 23 | 23 | 26 | 33 |
Good (51–100) 3 | 33 | 36 | 36 | 42 | 50 | 47 |
Lightly Polluted (101–150) 3 | 27 | 25 | 24 | 20 | 14 | 12 |
Moderately Polluted (151–200) 3 | 12 | 12 | 8 | 7 | 4 | 5 |
Heavily Polluted (201–300) 3 | 13 | 12 | 7 | 6 | 5 | 3 |
Severely Polluted (>300) 3 | 2 | 1 | 2 | 2 | 1 | 0 |
Year | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 |
---|---|---|---|---|---|---|
Moran’s I | 0.4 | 0.7 | 0.8 | 0.7 | 0.7 | 0.5 |
Detection Indices (X) | 2013 | 2014 | 2015 | 2016 | 2017 |
---|---|---|---|---|---|
Sown Area of Farm Crops (X1) | 0.6 | 0.6 | 0.5 | 0.4 | 0.5 |
Urban Green Area (X2) | 0.8 | 0.4 | 0.6 | 0.8 | 0.7 |
Gross Domestic Product (X3) | 0.2 | 0.2 | 0.3 | 0.2 | 0.4 |
Gross Domestic Product of Secondary Industry (X4) | 0.4 | 0.3 | 0.4 | 0.4 | 0.3 |
Completed Floor Space (X5) | 0.8 | 0.6 | 0.7 | 0.8 | 0.7 |
Population Density (X6) | 0.7 | 0.6 | 0.7 | 0.7 | 0.6 |
Car Ownership (X7) | 0.02 | 0.02 | 0.02 | 0.01 | 0.01 |
Average Wind Speed (X8) | 0.3 | 0.2 | 0.1 | 0.1 | 0.01 |
Relative Humidity (X9) | 0.4 | 0.4 | 0.4 | 0.3 | 0.4 |
Precipitation (X10) | 0.5 | 0.6 | 0.2 | 0.01 | 0.6 |
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Wang, L.; Xiong, Q.; Wu, G.; Gautam, A.; Jiang, J.; Liu, S.; Zhao, W.; Guan, H. Spatio-Temporal Variation Characteristics of PM2.5 in the Beijing–Tianjin–Hebei Region, China, from 2013 to 2018. Int. J. Environ. Res. Public Health 2019, 16, 4276. https://doi.org/10.3390/ijerph16214276
Wang L, Xiong Q, Wu G, Gautam A, Jiang J, Liu S, Zhao W, Guan H. Spatio-Temporal Variation Characteristics of PM2.5 in the Beijing–Tianjin–Hebei Region, China, from 2013 to 2018. International Journal of Environmental Research and Public Health. 2019; 16(21):4276. https://doi.org/10.3390/ijerph16214276
Chicago/Turabian StyleWang, Lili, Qiulin Xiong, Gaofeng Wu, Atul Gautam, Jianfang Jiang, Shuang Liu, Wenji Zhao, and Hongliang Guan. 2019. "Spatio-Temporal Variation Characteristics of PM2.5 in the Beijing–Tianjin–Hebei Region, China, from 2013 to 2018" International Journal of Environmental Research and Public Health 16, no. 21: 4276. https://doi.org/10.3390/ijerph16214276