Simulation of the Spatiotemporal Distribution of PM2.5 Concentration Based on GTWR-XGBoost Two-Stage Model: A Case Study of Chengdu Chongqing Economic Circle
Abstract
:1. Introduction
2. Research Methods and Data Sources
2.1. Research Area
2.2. Data and Processing
2.3. Research Methods
2.3.1. Model Principles
2.3.2. Variable Screening
2.3.3. Two-Stage Model Construction and Experimental Scheme Design
Model | Cross-Validation | Forecast Validation | ||||
---|---|---|---|---|---|---|
R2 | RMSE/ug·m−3 | MAE/ug·m−3 | R2 | RMSE/ug·m−3 | MAE/ug·m−3 | |
LUR | 0.68 | 10.72 | 8.06 | 0.63 | 11.16 | 8.55 |
GTWR | 0.82 | 7.65 | 5.42 | 0.78 | 8.64 | 5.82 |
RF | 0.80 | 8.49 | 6.33 | 0.75 | 9.28 | 6.74 |
XGBoost | 0.87 | 6.73 | 4.97 | 0.87 | 6.56 | 4.75 |
Model | Cross-Validation | Forecast Validation | ||||
---|---|---|---|---|---|---|
R2 | RMSE/ug·m−3 | MAE/u ug·m−3 | R2 | RMSE·ug/m−3 | MAE/ug·m−3 | |
LUR | 0.71 | 10.24 | 7.60 | 0.69 | 10.29 | 7.80 |
RF | 0.84 | 8.23 | 6.11 | 0.80 | 8.24 | 6.11 |
GTWR | 0.78 | 7.86 | 7.22 | 0.76 | 8.86 | 6.68 |
XGBoost | 0.91 | 5.60 | 4.23 | 0.90 | 5.59 | 3.99 |
Model | Cross-Validation | Forecast Validation | ||||
---|---|---|---|---|---|---|
R2 | RMSE/ug·m−3 | MAE/ug·m−3 | R2 | RMSE/ug·m−3 | MAE/ug·m−3 | |
STXGBoost [31] | 0.90 | 5.86 | 4.39 | 0.88 | 6.32 | 4.33 |
STRF [20] | 0.81 | 8.12 | 6.08 | 0.78 | 8.77 | 6.42 |
LUR-RF [21] | 0.82 | 7.85 | 5.92 | 0.78 | 8.76 | 6.52 |
LUR-XGBoost [29] | 0.90 | 5.99 | 4.63 | 0.87 | 6.60 | 4.81 |
GTWR-LUR | 0.85 | 7.24 | 5.50 | 0.82 | 7.81 | 5.72 |
GTWR-RF | 0.86 | 7.15 | 5.30 | 0.84 | 7.31 | 5.57 |
GTWR-XGBoost | 0.92 | 5.44 | 4.12 | 0.93 | 4.75 | 3.42 |
2.3.4. Accuracy Verification
3. Results and Analysis
3.1. Statistical Results
3.2. Model Comparison and Analysis
3.3. Spatiotemporal Distribution of PM2.5 Concentration in the Region
3.4. Analysis of Influencing Factors
4. Conclusions and Discussion
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
References
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Type | Name | English Abbreviations | Unit | Year | Spatial Resolution | Source |
---|---|---|---|---|---|---|
PM2.5 Monitoring data | Environmental monitoring station data | PM2.5 | ug·m−3 | 2018 | - | http://www.cnemc.cn/ (accessed on 10 December 2021) |
Natural environmental factors | Aerosol Optical Depth | AOD | - | 2018 | 1 km | https://ladsweb.modaps.eosdis.nasa.gov/ (accessed on 20 December 2021) |
Wind speed | WIN | m·s−1 | 2018 | 0.1° × 0.1° | http://data.tpdc.ac.cn/zh-hans/data/ (accessed on 20 December 2021) | |
Pressure | PRES | hPa | 2018 | |||
Temperature | TEM | K | 2018 | |||
air humidity ratio | SHUM | - | 2018 | |||
Precipitation | PREC | mm | 2018 | |||
Planetary Boundary Layer Height | PBLH | m | 2018 | 0.25° × 0.3° | ftp://rain.ucis.dal.ca/ctm/ (accessed on 20 December 2021) | |
Digital Elevation Model | DEM | m | 2018 | 90 m | http://www.gscloud.cn/search (accessed on 20 December 2021) | |
Normalized Difference Vegetation Index | NDVI | % | 2018 | 1 km | Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences (https://www.resdc.cn) (accessed on 20 December 2021) | |
Human activity intensity factor | population density | POP | - | 2018 | 100 m | World pop https://www.worldpop.org (accessed on 28 December 2021) |
Night light | NL | - | 2018 | 1.5 km | http://satsee.radi.ac.cn/cfimage/nightlight (accessed on 28 December 2021) | |
Road way | WAY | - | 2018 | - | http://www.openstreetmap.org (accessed on 28 December 2021) | |
Land use | LU | - | 2010 | 30 m | http://www.globallandcover.com (accessed on 28 December 2021) |
Variable | Correlation Coefficient | VIF Value |
---|---|---|
AOD | 0.32 | 1.17 |
WIN | −0.06 | 2.36 |
PRES | 0.20 | 3.12 |
TEM | −0.77 | 14.74 |
SHUM | −0.77 | 18.09 |
PREC | −0.65 | 2.68 |
PBLH | −0.70 | 2.11 |
DEM | −0.04 | 6.46 |
NDVI | −0.50 | 2.96 |
Variable | Average | Minimum | Maximum | Standard Deviation |
---|---|---|---|---|
PM2.5/ug m−3 | 41.38 | 4.99 | 112.43 | 18.95 |
WIN/m s−1 | 1.89 | 1.06 | 3.49 | 0.46 |
TEM/K | 290.99 | 274.54 | 305.23 | 7.5 |
SHUM | 0.018 | 0 | 0.03 | 0 |
PRES/hPa | 96,337.89 | 85,962 | 99,940 | 2333.02 |
PREC/mm | 0.18 | 0 | 0.79 | 0.12 |
AOD | 618.88 | 0 | 1798.25 | 433.43 |
PBLH/m | 674.61 | 296.48 | 892.52 | 168.89 |
NDVI | 0.38 | 0.018 | 0.888 | 0.17 |
dem/m | 390.33 | 199 | 1346 | 147.16 |
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Liu, M.; Luo, X.; Qi, L.; Liao, X.; Chen, C. Simulation of the Spatiotemporal Distribution of PM2.5 Concentration Based on GTWR-XGBoost Two-Stage Model: A Case Study of Chengdu Chongqing Economic Circle. Atmosphere 2023, 14, 115. https://doi.org/10.3390/atmos14010115
Liu M, Luo X, Qi L, Liao X, Chen C. Simulation of the Spatiotemporal Distribution of PM2.5 Concentration Based on GTWR-XGBoost Two-Stage Model: A Case Study of Chengdu Chongqing Economic Circle. Atmosphere. 2023; 14(1):115. https://doi.org/10.3390/atmos14010115
Chicago/Turabian StyleLiu, Minghao, Xiaolin Luo, Liai Qi, Xiangli Liao, and Chun Chen. 2023. "Simulation of the Spatiotemporal Distribution of PM2.5 Concentration Based on GTWR-XGBoost Two-Stage Model: A Case Study of Chengdu Chongqing Economic Circle" Atmosphere 14, no. 1: 115. https://doi.org/10.3390/atmos14010115