Assessing the Impact of Straw Burning on PM2.5 Using Explainable Machine Learning: A Case Study in Heilongjiang Province, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Fengyun-3 Series Global Active Fire Products
2.2. Land Cover
2.3. Auxiliary Data
2.3.1. Climate-Related Variables
2.3.2. DEM and AOD Data
2.3.3. ChinaHighPM2.5
2.4. Feature Selection
2.5. Random Forest Model
2.6. Interpretable Analysis
2.7. Data Preparation for Temporal and Spatial Models
3. Results and Discussion
3.1. Comparison with MODIS Fire Points
3.2. Spatial Distribution of Fire Points
3.3. Temporal Patterns and Variations
3.4. Monthly Variations in Crop Fire Points
3.5. Correlation and Collinearity Analyses of Input Features
3.6. Accuracy of the Temporal and Spatial Models
3.7. Impacts of Straw Burning and Other Influencing Factors on PM2.5
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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Xu, Z.; Liu, B.; Wang, W.; Zhang, Z.; Qiu, W. Assessing the Impact of Straw Burning on PM2.5 Using Explainable Machine Learning: A Case Study in Heilongjiang Province, China. Sustainability 2024, 16, 7315. https://doi.org/10.3390/su16177315
Xu Z, Liu B, Wang W, Zhang Z, Qiu W. Assessing the Impact of Straw Burning on PM2.5 Using Explainable Machine Learning: A Case Study in Heilongjiang Province, China. Sustainability. 2024; 16(17):7315. https://doi.org/10.3390/su16177315
Chicago/Turabian StyleXu, Zehua, Baiyin Liu, Wei Wang, Zhimiao Zhang, and Wenting Qiu. 2024. "Assessing the Impact of Straw Burning on PM2.5 Using Explainable Machine Learning: A Case Study in Heilongjiang Province, China" Sustainability 16, no. 17: 7315. https://doi.org/10.3390/su16177315