Spatiotemporal Distribution of Continuous Air Pollution and Its Relationship with Socioeconomic and Natural Factors in China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Source
2.2. Continuous Air Pollution Measurement
2.3. Spatial Analysis Methods
2.3.1. Bivariate Spatial Autocorrelation
2.3.2. Grouping Analysis
2.3.3. Multiscale Geographically Weighted Regression (MGWR)
3. Results
3.1. Descriptive Statistical
3.2. Spatial Distribution Characteristics of CAP
3.3. Temporal Distribution Characteristics of CAP
3.4. Region Types of the Major Pollutants during the CAP Periods
3.5. Spatial Heterogeneous Effects of the Driving Forces on CAP
3.5.1. Goodness of Fit and Bandwidth
3.5.2. Estimated Parameter Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Air Quality Index (AQI) | Air Quality Index Level | Air Quality Index Category | Major Pollutants |
---|---|---|---|
0–50 | Level 1 | Excellent | SO2, NO2, CO, O3, PM10, PM2.5 |
51–100 | Level 2 | Good | |
101–150 | Level 3 | Light pollution | |
151–200 | Level 4 | Moderate pollution | |
201–300 | Level 5 | Heavy pollution | |
>300 | Level 6 | Serious pollution |
Measurement Indicators | Mean | Std. Dev. | Min | Max |
---|---|---|---|---|
Proportion of air pollution days (%) | 17.80 | 16 | 0.00 | 78.36 |
Proportion of CAP days (%) | 11.50 | 13 | 0.00 | 73.15 |
Frequency of CAP (times) | 8.02 | 8.06 | 0.00 | 29.00 |
Maximum of CAP days (days) | 7.85 | 6.96 | 0.00 | 64.00 |
Average of CAP days (days) | 4.20 | 2.41 | 0.00 | 16.69 |
Types of Regions | PM10 | O3 | PM2.5 | NO2 | Count | Types |
---|---|---|---|---|---|---|
Group 1 | 7.28 | 58.17 | 56.58 | 0.06 | 53 | Composite pollution |
Group 2 | 0.00 | 32.11 | 0.22 | 3.11 | 9 | O3 + NO2 pollution |
Group 3 | 130.33 | 0.67 | 28.83 | 0.00 | 6 | PM10 + PM2.5 pollution |
Group 4 | 1.20 | 8.46 | 13.87 | 0.14 | 269 | O3 + PM2.5 pollution |
Mean | 4.43 | 16.77 | 20.49 | 0.20 | 337 |
Goodness of Fit Statistic | OLS | GWR | MGWR |
---|---|---|---|
Residual sum of squares | 168.862 | 34.963 | 35.712 |
Log likelihood | −362.321 | −96.184 | −99.764 |
AIC | 752.642 | 388.233 | 358.079 |
AICc | 756.133 | 469.288 | 407.464 |
R2 | 0.5 | 0.897 | 0.894 |
Adj. R2 | 0.48 | 0.855 | 0.862 |
BIC | 762.635 | 661.153 | |
Degree of Dependency (DoD) | 0.668 | 0.704 |
Variable | OLS Model | MGWR Model | ||||
---|---|---|---|---|---|---|
Est. | Mean | STD | Min | Median | Max | |
Intercept | 0.000 | 0.885 | 0.356 | 0.396 | 0.772 | 1.779 |
popden | −0.006 | 0.173 | 0.213 | −0.055 | 0.068 | 0.596 |
pgdp | −0.173 *** | 0.008 | 0.095 | −0.320 | 0.019 | 0.166 |
prosec | −0.015 | −0.030 | 0.023 | −0.104 | −0.021 | −0.011 |
FDI | 0.115 ** | −0.040 | 0.004 | −0.054 | −0.039 | −0.035 |
NDVI | −0.141 ** | −0.204 | 0.011 | −0.247 | −0.203 | −0.186 |
roadden | 0.208 *** | −0.014 | 0.001 | −0.022 | −0.014 | −0.011 |
energy | 0.069 | 0.022 | 0.154 | −0.392 | 0.013 | 0.417 |
tem | 0.230 *** | −0.437 | 0.324 | −0.833 | −0.466 | 0.079 |
pre | −0.541 *** | 0.015 | 0.183 | −0.236 | −0.036 | 0.361 |
ws | −0.149 ** | 0.056 | 0.223 | −0.571 | 0.085 | 0.443 |
rh | −0.461 *** | −0.080 | 0.287 | −0.810 | −0.088 | 0.490 |
ap | 0.435 *** | 0.535 | 0.089 | 0.403 | 0.518 | 0.658 |
sd | −0.315 *** | −0.019 | 0.127 | −0.271 | 0.050 | 0.103 |
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Zhan, D.; Zhang, Q.; Xu, X.; Zeng, C. Spatiotemporal Distribution of Continuous Air Pollution and Its Relationship with Socioeconomic and Natural Factors in China. Int. J. Environ. Res. Public Health 2022, 19, 6635. https://doi.org/10.3390/ijerph19116635
Zhan D, Zhang Q, Xu X, Zeng C. Spatiotemporal Distribution of Continuous Air Pollution and Its Relationship with Socioeconomic and Natural Factors in China. International Journal of Environmental Research and Public Health. 2022; 19(11):6635. https://doi.org/10.3390/ijerph19116635
Chicago/Turabian StyleZhan, Dongsheng, Qianyun Zhang, Xiaoren Xu, and Chunshui Zeng. 2022. "Spatiotemporal Distribution of Continuous Air Pollution and Its Relationship with Socioeconomic and Natural Factors in China" International Journal of Environmental Research and Public Health 19, no. 11: 6635. https://doi.org/10.3390/ijerph19116635